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Updated my HF Space for vibe testing smol VLMs on object detection, visual grounding, keypoint detection & counting! 👓 🆕Compare Qwen2.5 VL 3B vs Moondream 2B side-by-side with annotated images & text outputs. Try examples or test your own images! 🏃👇

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Sergio Paniego

2,567 subscribers

15,717 次观看 • 1 年前 •via X (Twitter)

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Sergio Paniego 的头像
Sergio Paniego1 年前

📱Space: Models by @Alibaba_Qwen and @moondreamai!

merve 的头像
merve1 年前

@skalskip92 @vikhyatk @JustinLin610 @onuralpszr you have to see this ^

vik 的头像
vik1 年前

for moondream object detection prompting with just the object name will work better, that's how we train it

Sergio Paniego 的头像
Sergio Paniego1 年前

I was unsure whether to use the full prompt or just the object name for the examples. Let me update it to make the comparison fairer 😃

Andres Franco 的头像
Andres Franco1 年前

That’s impressive. Playing around with models like that must be a lot of fun.

Prithiv Sakthi 🌠 的头像
Prithiv Sakthi 🌠1 年前

This is really awesome 🤩

Reza Sayar 的头像
Reza Sayar1 年前

awesome! 👏 very useful work!! 🥳🙏

Linus | web3 mobility network nRide 的头像
Linus | web3 mobility network nRide1 年前

@pcuenq Vibe testing VLMs, that's really cool! I'm curious, have you explored any blockchain-based applications for object detection or visual grounding? 🤔

Onuralp S. 的头像
Onuralp S.1 年前

I was experimenting with qwen and I can see it can detect each individual candies and when I ask a little bit differently it always says "colorful candies" and when I put that in to prompt I get some what better results but when I say return as "json" it just become one bbox

Johannes Gilger 的头像
Johannes Gilger1 年前

This is awesome, thank you so much for that. Also really helps to show the inference time. Now do all the other small-ish VLMs like Molmo, SmolVLM, InternVL, etc 😅

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PDF parsing is still painful because LLMs reorder text in complex layouts, break tables across pages, and fail on graphs or images. 💡Testing the new open-source OCRFlux model, and here the results are really good for a change. So OCRFlux is a multimodal, LLM based toolkit for converting PDFs and images into clean, readable, plain Markdown text. Because the underlying VLM is only 3B param, it runs even on a 3090 GPU. The model is available on Hugging Face . The engine that powers the OCRFlux, teaches the model to rebuild every page and then stitch fragments across pages into one clean Markdown file. It bundles one vision language model with 3B parameters that was fine-tuned from Qwen 2.5-VL-3B-Instruct for both page parsing and cross-page merging. OCRFlux reads raw page images and, guided by task prompts, outputs Markdown for each page and merges split elements across pages. The evaluation shows Edit Distance Similarity (EDS) 0.967 and cross‑page table Tree Edit Distance 0.950, so the parser is both accurate and layout aware. How it works while parsing each page - Convert into text with a natural reading order, even in the presence of multi-column layouts, figures, and insets - Support for complicated tables and equations - Automatically removes headers and footers Cross-page table/paragraph merging - Cross-page table merging - Cross-page paragraph merging A compact vision‑language models can beat bigger models once cross‑page context is added. 🧵 1/n Read on 👇
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PDF parsing is still painful because LLMs reorder text in complex layouts, break tables across pages, and fail on graphs or images. 💡Testing the new open-source OCRFlux model, and here the results are really good for a change. So OCRFlux is a multimodal, LLM based toolkit for converting PDFs and images into clean, readable, plain Markdown text. Because the underlying VLM is only 3B param, it runs even on a 3090 GPU. The model is available on Hugging Face . The engine that powers the OCRFlux, teaches the model to rebuild every page and then stitch fragments across pages into one clean Markdown file. It bundles one vision language model with 3B parameters that was fine-tuned from Qwen 2.5-VL-3B-Instruct for both page parsing and cross-page merging. OCRFlux reads raw page images and, guided by task prompts, outputs Markdown for each page and merges split elements across pages. The evaluation shows Edit Distance Similarity (EDS) 0.967 and cross‑page table Tree Edit Distance 0.950, so the parser is both accurate and layout aware. How it works while parsing each page - Convert into text with a natural reading order, even in the presence of multi-column layouts, figures, and insets - Support for complicated tables and equations - Automatically removes headers and footers Cross-page table/paragraph merging - Cross-page table merging - Cross-page paragraph merging A compact vision‑language models can beat bigger models once cross‑page context is added. 🧵 1/n Read on 👇

Rohan Paul

149,292 次观看 • 1 年前

Everyone is sleeping on Meta's SAM 3 release. But it's actually a big deal. Here's why: Companies spend millions paying humans to label images and videos frame by frame. A single autonomous driving dataset? Months of work, hundreds of annotators, millions in cost. Without labeled data, you can't train custom models. Without custom models, you're stuck with generic solutions. This is why most companies never move past pilots. SAM 3 breaks this cycle. First let's look at the evolution: SAM 1 segmented objects when you clicked on them. Revolutionary, but one object at a time. SAM 2 added video tracking with memory. Game-changing, but you still manually prompted every object. SAM 3 changes everything with text prompts. Type "yellow school bus" and it finds ALL of them in your image or video. Not just one. Every instance across thousands of frames. Now here's where people get confused: "Can't I just use GPT-5 or Gemini for this?" No, and here's why that's a terrible approach. Large multimodal LLMs are great for reasoning, but they're slow and expensive for production visual tasks. You're paying API costs per image, waiting seconds for responses, getting inconsistent results. SAM 3 runs in 30 milliseconds on a single GPU for 100+ objects. That's 100x faster, and you own the infrastructure. More importantly, SAM 3 gives you precise pixel-level masks, not descriptions. Try asking an LLM to segment every defective part on a manufacturing line in real-time. It won't work. SAM 3 does this effortlessly. The real breakthrough is their data engine. Meta built an AI-human hybrid system that's 5x faster for complex annotations. They trained SAM 3 on 4 million unique visual concepts - 50x more than existing benchmarks like LVIS. SAM 3 is trained on 4 million unique visual concepts, it handles everything: - Text-based concept search - Interactive refinement with clicks - Video tracking across frames - Zero-shot detection of new concepts The model is open source. Weights, code, and benchmarks are on GitHub. If you're building computer vision applications, this is the foundation model to evaluate. The annotation time savings alone will pay for integration costs within weeks. Find the relevant links in the next tweet!
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Everyone is sleeping on Meta's SAM 3 release. But it's actually a big deal. Here's why: Companies spend millions paying humans to label images and videos frame by frame. A single autonomous driving dataset? Months of work, hundreds of annotators, millions in cost. Without labeled data, you can't train custom models. Without custom models, you're stuck with generic solutions. This is why most companies never move past pilots. SAM 3 breaks this cycle. First let's look at the evolution: SAM 1 segmented objects when you clicked on them. Revolutionary, but one object at a time. SAM 2 added video tracking with memory. Game-changing, but you still manually prompted every object. SAM 3 changes everything with text prompts. Type "yellow school bus" and it finds ALL of them in your image or video. Not just one. Every instance across thousands of frames. Now here's where people get confused: "Can't I just use GPT-5 or Gemini for this?" No, and here's why that's a terrible approach. Large multimodal LLMs are great for reasoning, but they're slow and expensive for production visual tasks. You're paying API costs per image, waiting seconds for responses, getting inconsistent results. SAM 3 runs in 30 milliseconds on a single GPU for 100+ objects. That's 100x faster, and you own the infrastructure. More importantly, SAM 3 gives you precise pixel-level masks, not descriptions. Try asking an LLM to segment every defective part on a manufacturing line in real-time. It won't work. SAM 3 does this effortlessly. The real breakthrough is their data engine. Meta built an AI-human hybrid system that's 5x faster for complex annotations. They trained SAM 3 on 4 million unique visual concepts - 50x more than existing benchmarks like LVIS. SAM 3 is trained on 4 million unique visual concepts, it handles everything: - Text-based concept search - Interactive refinement with clicks - Video tracking across frames - Zero-shot detection of new concepts The model is open source. Weights, code, and benchmarks are on GitHub. If you're building computer vision applications, this is the foundation model to evaluate. The annotation time savings alone will pay for integration costs within weeks. Find the relevant links in the next tweet!

Akshay 🚀

46,421 次观看 • 8 个月前

Google Search Console gives you numbers. GSC Wizard gives you answers. Decades of doing data driven SEO. Every week I'd export GSC data, wrangle it in spreadsheets, try to find the story in the numbers. Then do it again for the next client. And again. So I built the tool I always wanted: GSC Wizard turns raw Search Console data into actionable intelligence. No spreadsheet gymnastics required. Here's every feature and what it actually solves: ◆ SITE RESTRUCTURING & TOPICAL MAPPING BERTopic clustering with multilingual-e5-large-instruct embeddings maps your entire site into topic clusters. Visual drag-and-drop tree hierarchy lets you redesign site architecture. Auto-generates redirect maps, internal linking plans, and content briefs for gaps. Works across languages so you can see coverage gaps per topic per market at a glance. ◆ CANNIBALIZATION DETECTION Detects when pages compete for the same keywords. Not just keyword overlap, but intent-level conflicts. Shows which URL should win and which should merge or redirect. ◆ CONTENT DECAY MONITORING Visualizes which pages are losing traffic over time with an intuitive heatmap. Spot declining content before it's too late. ◆ FORECASTING Predict future organic traffic based on historical GSC trends. Model scenarios for content investments, seasonal patterns, and growth targets. ◆ ANOMALY DETECTION Automatically flags unusual spikes or drops in clicks, impressions, CTR, and position. No more finding out a month later that something broke. ◆ MIGRATION DASHBOARDS Track performance before and after domain, folder or URL migrations across multiple GSC properties. Monitor traffic recovery, catch URL mapping gaps, and compare old vs. new property data side by side. The cross-property view is critical for enterprise migrations that nobody else handles properly. ◆ EXPERIMENT MONITORING Run A/B tests on title tags, meta descriptions, and content changes. Measure impact with statistical significance testing and group comparisons. Prove that your SEO changes actually worked. ◆ INTERNATIONAL ANALYSIS Analyze performance across countries and languages. Detect country-level cannibalization, and compare properties across markets. Cross-property analysis shows you which markets are underserved. ◆ INDEXING MONITOR Track which pages Google is picking up and which ones are quietly disappearing from the index. ◆ PAGE POACHING OPPORTUNITIES Find keywords ranking at positions 4-20 that are ripe for pushing into the top 3 with small optimizations. ◆ ON-PAGE CHECKS Check if top queries appear in titles, meta descriptions, and H1 headings. Simple but surprisingly powerful. ◆ KEYWORD CLUSTERING Group related keywords into clusters and track aggregate performance. See which topics drive the most traffic and where clusters are thin. Every report surfaces specific opportunities. Sign up for the waiting list now.
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Google Search Console gives you numbers. GSC Wizard gives you answers. Decades of doing data driven SEO. Every week I'd export GSC data, wrangle it in spreadsheets, try to find the story in the numbers. Then do it again for the next client. And again. So I built the tool I always wanted: GSC Wizard turns raw Search Console data into actionable intelligence. No spreadsheet gymnastics required. Here's every feature and what it actually solves: ◆ SITE RESTRUCTURING & TOPICAL MAPPING BERTopic clustering with multilingual-e5-large-instruct embeddings maps your entire site into topic clusters. Visual drag-and-drop tree hierarchy lets you redesign site architecture. Auto-generates redirect maps, internal linking plans, and content briefs for gaps. Works across languages so you can see coverage gaps per topic per market at a glance. ◆ CANNIBALIZATION DETECTION Detects when pages compete for the same keywords. Not just keyword overlap, but intent-level conflicts. Shows which URL should win and which should merge or redirect. ◆ CONTENT DECAY MONITORING Visualizes which pages are losing traffic over time with an intuitive heatmap. Spot declining content before it's too late. ◆ FORECASTING Predict future organic traffic based on historical GSC trends. Model scenarios for content investments, seasonal patterns, and growth targets. ◆ ANOMALY DETECTION Automatically flags unusual spikes or drops in clicks, impressions, CTR, and position. No more finding out a month later that something broke. ◆ MIGRATION DASHBOARDS Track performance before and after domain, folder or URL migrations across multiple GSC properties. Monitor traffic recovery, catch URL mapping gaps, and compare old vs. new property data side by side. The cross-property view is critical for enterprise migrations that nobody else handles properly. ◆ EXPERIMENT MONITORING Run A/B tests on title tags, meta descriptions, and content changes. Measure impact with statistical significance testing and group comparisons. Prove that your SEO changes actually worked. ◆ INTERNATIONAL ANALYSIS Analyze performance across countries and languages. Detect country-level cannibalization, and compare properties across markets. Cross-property analysis shows you which markets are underserved. ◆ INDEXING MONITOR Track which pages Google is picking up and which ones are quietly disappearing from the index. ◆ PAGE POACHING OPPORTUNITIES Find keywords ranking at positions 4-20 that are ripe for pushing into the top 3 with small optimizations. ◆ ON-PAGE CHECKS Check if top queries appear in titles, meta descriptions, and H1 headings. Simple but surprisingly powerful. ◆ KEYWORD CLUSTERING Group related keywords into clusters and track aggregate performance. See which topics drive the most traffic and where clusters are thin. Every report surfaces specific opportunities. Sign up for the waiting list now.

Jan-Willem Bobbink

24,221 次观看 • 4 个月前

I just vibe coded a static ad generator in Claude Code that creates 100+ Facebook ads in minutes 🤯 All using the new insane ChatGPT Images 2.0 model. Upload one image of your brand or product → get 100+ brand-new ad concepts across every DR archetype, each one matched to a specific customer persona. Built 100% in Claude Code. Perfect for DTC brands and agencies who need to rapidly test mass creative statics at scale. Here's how it works: → Upload a single image of your brand or product → Add your brand kit (colors, fonts, logos) → Tool generates 10 customer personas from your brand research (Depleted Woman, Burned-Out Professional, Brain-Fogged Mom) → Pick how many concepts you want (40, 60, 100+) across archetypes — Bold Billboard, Listicle, iPhone Notes, iMessage, UI Hijack, Us vs Them, Press/Authority, Lo-Fi Sketch, UGC → Hit "Generate All" → finished ads render in seconds, each one targeting a specific persona with its own copy angle No more paying "static ad agencies" $3,000 per month. What you get: - 100+ on-brand static ads from a single product photo - Perfect product and text adherence powered by ChatGPT Images 2.0 - Persona-specific copy on every ad, no generic hooks - Iterate and scale statics in minutes instead of weeks - Reusable brand kits + persona libraries you build once and pull from forever - Every ad ships with the exact prompt and persona attached, so you can iterate instead of starting over. This is essentially a static ad agency in a box. I put together a complete playbook which includes EVERY single prompt I used to make this in Claude Code. Want all the prompts for free? > Like this post > Comment "STATICS" And I'll send it over (must be following so I can DM)
0:48

I just vibe coded a static ad generator in Claude Code that creates 100+ Facebook ads in minutes 🤯 All using the new insane ChatGPT Images 2.0 model. Upload one image of your brand or product → get 100+ brand-new ad concepts across every DR archetype, each one matched to a specific customer persona. Built 100% in Claude Code. Perfect for DTC brands and agencies who need to rapidly test mass creative statics at scale. Here's how it works: → Upload a single image of your brand or product → Add your brand kit (colors, fonts, logos) → Tool generates 10 customer personas from your brand research (Depleted Woman, Burned-Out Professional, Brain-Fogged Mom) → Pick how many concepts you want (40, 60, 100+) across archetypes — Bold Billboard, Listicle, iPhone Notes, iMessage, UI Hijack, Us vs Them, Press/Authority, Lo-Fi Sketch, UGC → Hit "Generate All" → finished ads render in seconds, each one targeting a specific persona with its own copy angle No more paying "static ad agencies" $3,000 per month. What you get: - 100+ on-brand static ads from a single product photo - Perfect product and text adherence powered by ChatGPT Images 2.0 - Persona-specific copy on every ad, no generic hooks - Iterate and scale statics in minutes instead of weeks - Reusable brand kits + persona libraries you build once and pull from forever - Every ad ships with the exact prompt and persona attached, so you can iterate instead of starting over. This is essentially a static ad agency in a box. I put together a complete playbook which includes EVERY single prompt I used to make this in Claude Code. Want all the prompts for free? > Like this post > Comment "STATICS" And I'll send it over (must be following so I can DM)

Mike Futia

107,259 次观看 • 2 个月前

My fox shooting garden defending AI robot is finally done and WORKING! 🤩 (Don’t worry it only shoots 💦 water) After months of slowly moving forward with each part I finished the last step to train a TensorFlow model on the footage of the 🦊 fox I collected hours of footage 📹 with the fox roaming around my garden, from this I labeled around 2000 images with the fox by hand ✋ Honestly, I was quite skeptical training the model was actually gonna work, maybe this was partly the reason I avoided working on this until the very end. If I couldn’t train a model to detect the fox, this whole robot would never be able to function properly. On the flipside though, with no previous experience in hardware or electronics there was a bit of a learning curve and I didn’t want to end up labeling thousands of images, training a TensorFlow model, only to fail on building the hardware. As I started building, I realized that mixing hardware and software adds quite another dimension to debugging things. At times I wasted hours debugging code in my IDE, only to realize the issue was somewhere in the electronics. Furthermore, combining this side project with a full time job and a young family, is not always easy. It can be quite frustrating, to know you only need 4 hours of concentrated effort for a small task, having to spread it out across a week of 20min increments. Then, a few months into the build I noticed the fox had stopped coming to my garden, in fact one day, I recorded her walking with 3 cute little 🐶 pups, and the next day I saw her moving out of my garden completely. Did she know I was building a robot? I had this strange mix of feelings, happy my garden was safe from poop and digging, happy she was safe with her pups, but how was I gonna finish this project if my robot had no fox to detect? For sure they would be back next year, I figured I could postpone the whole thing until next winter, but I also knew it was gonna be much harder to pick up momentum if I did let it sit there for six months. So I decided to keep working, hoping the fox would reappear,.. but she never did. As I finished labeling the footage and started training my model, I could finally see the mAP results, quantifying the precision of my object detection model. It was measuring at 78% across different metrics on detecting my fox. I quickly ran the model on some of the video footage I got from my fox. Inference speed took a hit, but it did a near perfect job detecting the fox, even when she was deep down in the grass or wizzing past in a motion blur. It took me by surprise how well it worked. With the default model I had to drop my confidence threshold way down to 15%, to recognize the fox as 🦜“bird” in one or two frames, with my custom model it followed the fox all the way down to the back of the garden! Still this didn’t solve the issue of there being no actual fox in my garden and how was I gonna wrap this project in a short timeframe. I played with the idea of putting a fox toy 🧸 on an RC 🚗 car, or borrowing a dog to run around the garden to test. Friends suggested I run around the garden in a fox costume.. what a ridiculous idea. I wasn’t really feeling the idea of running around the garden in a floppy cloth fox 🎭 costume, but had a look anyway. I came across these self inflating costumes. This actually could be perfect. Since it’s inflated, it would hold its shape super well, making it much easier to label, train and be recognized by my robot. So I got the costume and shot a time lapse of myself as a fox walking around the garden. I labeled it to around 600 images. Ran the model training again and got a mAP result of 82%. This was even better than my real fox! At this point I knew this was gonna work. So here’s the final 🎥 video, just having some fun with it. I’ll update here whenever the real fox does come back. On a final note, I’m looking for (remote) jobs in these fields of AI now: - object detection - visual generative AI - 3D (nerfs + gaussian splats) So if you know anything let me know! My DMs are open 😊
2:05

My fox shooting garden defending AI robot is finally done and WORKING! 🤩 (Don’t worry it only shoots 💦 water) After months of slowly moving forward with each part I finished the last step to train a TensorFlow model on the footage of the 🦊 fox I collected hours of footage 📹 with the fox roaming around my garden, from this I labeled around 2000 images with the fox by hand ✋ Honestly, I was quite skeptical training the model was actually gonna work, maybe this was partly the reason I avoided working on this until the very end. If I couldn’t train a model to detect the fox, this whole robot would never be able to function properly. On the flipside though, with no previous experience in hardware or electronics there was a bit of a learning curve and I didn’t want to end up labeling thousands of images, training a TensorFlow model, only to fail on building the hardware. As I started building, I realized that mixing hardware and software adds quite another dimension to debugging things. At times I wasted hours debugging code in my IDE, only to realize the issue was somewhere in the electronics. Furthermore, combining this side project with a full time job and a young family, is not always easy. It can be quite frustrating, to know you only need 4 hours of concentrated effort for a small task, having to spread it out across a week of 20min increments. Then, a few months into the build I noticed the fox had stopped coming to my garden, in fact one day, I recorded her walking with 3 cute little 🐶 pups, and the next day I saw her moving out of my garden completely. Did she know I was building a robot? I had this strange mix of feelings, happy my garden was safe from poop and digging, happy she was safe with her pups, but how was I gonna finish this project if my robot had no fox to detect? For sure they would be back next year, I figured I could postpone the whole thing until next winter, but I also knew it was gonna be much harder to pick up momentum if I did let it sit there for six months. So I decided to keep working, hoping the fox would reappear,.. but she never did. As I finished labeling the footage and started training my model, I could finally see the mAP results, quantifying the precision of my object detection model. It was measuring at 78% across different metrics on detecting my fox. I quickly ran the model on some of the video footage I got from my fox. Inference speed took a hit, but it did a near perfect job detecting the fox, even when she was deep down in the grass or wizzing past in a motion blur. It took me by surprise how well it worked. With the default model I had to drop my confidence threshold way down to 15%, to recognize the fox as 🦜“bird” in one or two frames, with my custom model it followed the fox all the way down to the back of the garden! Still this didn’t solve the issue of there being no actual fox in my garden and how was I gonna wrap this project in a short timeframe. I played with the idea of putting a fox toy 🧸 on an RC 🚗 car, or borrowing a dog to run around the garden to test. Friends suggested I run around the garden in a fox costume.. what a ridiculous idea. I wasn’t really feeling the idea of running around the garden in a floppy cloth fox 🎭 costume, but had a look anyway. I came across these self inflating costumes. This actually could be perfect. Since it’s inflated, it would hold its shape super well, making it much easier to label, train and be recognized by my robot. So I got the costume and shot a time lapse of myself as a fox walking around the garden. I labeled it to around 600 images. Ran the model training again and got a mAP result of 82%. This was even better than my real fox! At this point I knew this was gonna work. So here’s the final 🎥 video, just having some fun with it. I’ll update here whenever the real fox does come back. On a final note, I’m looking for (remote) jobs in these fields of AI now: - object detection - visual generative AI - 3D (nerfs + gaussian splats) So if you know anything let me know! My DMs are open 😊

Jeroen Pixel

55,797 次观看 • 2 年前

How to Build a Proper Product Page It breaks my heart every time I see someone from Brazil, making just $200 a month, spend $40 on a test ad only to get a $2 CPC. Then, they cut the ad at $35 spend with 17 clicks and 0 conversions. What’s even more frustrating is when I visit their site and see it’s a complete mess. It’s like they didn’t even try. That’s why I’m making this post. *Disclaimer: If you're building a brand, this isn’t for you. This is for testing products correctly with a website that’s good enough to convert, but if you’re serious about your brand, hire a Figma designer and a developer to get things done right. As a fun fact, I tested the following product myself (In the video below) and with just one click at a $3 CPC, I got a sale with an $80 AOV (100% CVR). I paused the ads because the CPMs hit $150. If you're interested, save this product for the future. I'll share the creatives i used to ran the product with those who comment below. "jordan, stop teaching high school kids about selling reps and getting them sued by Prada or other big brands, ruining their payment gateways, and crushing their dreams." (with 5 random people only will do it, wouldn't make sense for everyone to be ripping it). Shoutout to Adrian for this one. 🫡 Back to the important stuff: Let’s talk about creating a great product page. First off, ditch the “Buy Now” button. By using this, you miss out on the chance to increase your Average Order Value (AOV) through upsells during checkout. Instead, replace it with an “Add to Cart” button. Also, remove the quantity selector. Hardly anyone uses them on the product page, but they do in the cart. Instead, offer bundles, which you can set up using the Kaching Bundles app or your theme if it supports this feature. The cart experience is crucial, and you can optimize it using the UpCart app. Enable all its product page features so it takes over the standard Shopify cart or your theme’s cart. The built-in cart systems are outdated—they don’t allow upsells like UpCart does. Plus, UpCart directly opens the cart after a product is added, where the upsell option appears at the bottom, increasing your chances of boosting AOV. Pay attention to color schemes. Don’t use neutral colors for headers and buttons if your product features a primary color. A yellow jacket with a black header is like pizza with raspberry syrup—just doesn’t work. If your product images are gray, white, or black, match those with your headers and buttons. Otherwise, play around with colors to give your page some dynamic appeal. Bookmark this site to get color palettes that match your primary color. For exact color matches, download the "ColorZilla" extension, which gives you the exact color code of whatever is under your mouse on the screen. If your product color is #6E402A, you’ll know it and can match it perfectly with your header and buttons, creating a visually appealing contrast like Cider did here below. Right now, when some of you send me these websites, they look like government pages from the early 2000s. Next, consider the typography and button styles. For fonts, use Helvetica Regular for body text and Helvetica Bold for titles, both at a minimum size of 100%. It’s simple and effective. As for buttons, they should have a corner radius of 8px. To change these settings, go to the theme settings - typography/buttons and adjust the buttons and typography accordingly. Rounded buttons create a modern, inviting feel, while full square buttons can give off an outdated vibe. Even casinos in Vegas design their buildings with curves, ensuring that visitors always have a view angle that draws them back in—it’s all about keeping things appealing and engaging. Finally, the product page layout itself should be clean and concise. Use collapsible rows for your product descriptions. No one wants to read a novel, so keep it compact and focused. Images and videos are what sell—this is why we don’t use text-heavy images in our ads; they just bore people. Keep the description short, with enough information to inform but not overwhelm. If you need to include more features, put them in the FAQs section—that’s what they’re for. The goal is to make sure that the "Add to Cart" button is visible as soon as possible once the customer lands on the product page, without overwhelming them but providing just enough information—some key benefits, high-quality images, and buying options in the bundles. Once they hit the cart, the upsells will do their job. Remember, the three essential apps for setting this up are Loox Reviews for customer feedback (use the product widget reviews at the bottom of the page before the FAQs and the rating widget just above the title), Kaching Bundles for offering package deals, and UpCart for optimizing the cart experience. Just for the record, this is to help newcomers and guide them to something taht works, me personally i don't use free themes, but this one i created could convert easily if the product, offer and ads match well. Good luck and keep testing! 🗳🥂💸🤑
0:23

How to Build a Proper Product Page It breaks my heart every time I see someone from Brazil, making just $200 a month, spend $40 on a test ad only to get a $2 CPC. Then, they cut the ad at $35 spend with 17 clicks and 0 conversions. What’s even more frustrating is when I visit their site and see it’s a complete mess. It’s like they didn’t even try. That’s why I’m making this post. *Disclaimer: If you're building a brand, this isn’t for you. This is for testing products correctly with a website that’s good enough to convert, but if you’re serious about your brand, hire a Figma designer and a developer to get things done right. As a fun fact, I tested the following product myself (In the video below) and with just one click at a $3 CPC, I got a sale with an $80 AOV (100% CVR). I paused the ads because the CPMs hit $150. If you're interested, save this product for the future. I'll share the creatives i used to ran the product with those who comment below. "jordan, stop teaching high school kids about selling reps and getting them sued by Prada or other big brands, ruining their payment gateways, and crushing their dreams." (with 5 random people only will do it, wouldn't make sense for everyone to be ripping it). Shoutout to Adrian for this one. 🫡 Back to the important stuff: Let’s talk about creating a great product page. First off, ditch the “Buy Now” button. By using this, you miss out on the chance to increase your Average Order Value (AOV) through upsells during checkout. Instead, replace it with an “Add to Cart” button. Also, remove the quantity selector. Hardly anyone uses them on the product page, but they do in the cart. Instead, offer bundles, which you can set up using the Kaching Bundles app or your theme if it supports this feature. The cart experience is crucial, and you can optimize it using the UpCart app. Enable all its product page features so it takes over the standard Shopify cart or your theme’s cart. The built-in cart systems are outdated—they don’t allow upsells like UpCart does. Plus, UpCart directly opens the cart after a product is added, where the upsell option appears at the bottom, increasing your chances of boosting AOV. Pay attention to color schemes. Don’t use neutral colors for headers and buttons if your product features a primary color. A yellow jacket with a black header is like pizza with raspberry syrup—just doesn’t work. If your product images are gray, white, or black, match those with your headers and buttons. Otherwise, play around with colors to give your page some dynamic appeal. Bookmark this site to get color palettes that match your primary color. For exact color matches, download the "ColorZilla" extension, which gives you the exact color code of whatever is under your mouse on the screen. If your product color is #6E402A, you’ll know it and can match it perfectly with your header and buttons, creating a visually appealing contrast like Cider did here below. Right now, when some of you send me these websites, they look like government pages from the early 2000s. Next, consider the typography and button styles. For fonts, use Helvetica Regular for body text and Helvetica Bold for titles, both at a minimum size of 100%. It’s simple and effective. As for buttons, they should have a corner radius of 8px. To change these settings, go to the theme settings - typography/buttons and adjust the buttons and typography accordingly. Rounded buttons create a modern, inviting feel, while full square buttons can give off an outdated vibe. Even casinos in Vegas design their buildings with curves, ensuring that visitors always have a view angle that draws them back in—it’s all about keeping things appealing and engaging. Finally, the product page layout itself should be clean and concise. Use collapsible rows for your product descriptions. No one wants to read a novel, so keep it compact and focused. Images and videos are what sell—this is why we don’t use text-heavy images in our ads; they just bore people. Keep the description short, with enough information to inform but not overwhelm. If you need to include more features, put them in the FAQs section—that’s what they’re for. The goal is to make sure that the "Add to Cart" button is visible as soon as possible once the customer lands on the product page, without overwhelming them but providing just enough information—some key benefits, high-quality images, and buying options in the bundles. Once they hit the cart, the upsells will do their job. Remember, the three essential apps for setting this up are Loox Reviews for customer feedback (use the product widget reviews at the bottom of the page before the FAQs and the rating widget just above the title), Kaching Bundles for offering package deals, and UpCart for optimizing the cart experience. Just for the record, this is to help newcomers and guide them to something taht works, me personally i don't use free themes, but this one i created could convert easily if the product, offer and ads match well. Good luck and keep testing! 🗳🥂💸🤑

Zzzz

42,318 次观看 • 1 年前

Remember that paper that started with ‘Certainly, here is a possible introduction for your topic’? How did that get past peer review?! I don’t want AI tools to do my research for me. I want AI tools to speed up boring tasks that take up my time, so I can focus on the important stuff. Anara moved to a new handle (formerly Unriddle) does exactly that. Here’s how you can use it for your research. 🧵👇 #SponsoredWalkthrough One of the biggest challenges in research is time. A solid literature review takes at least 2-3 months… sometimes even longer, depending on the depth of analysis needed. Reading, organising, and synthesising information is a slow process, but it’s absolutely necessary for high-quality work. AI can help speed it up. Not by replacing your critical thinking. It’s your PhD, your ideas need to be your own—but by automating the tedious, repetitive parts of research so you can focus on deep understanding, analysis, and writing. Unlike other AI tools, Anara works with almost any document format. This is what makes it really stand out from the rest. For instance, you can upload: ✅PDFs and other word-based documents ✅Images and presentations ✅Handwritten notes, voice memos, even videos There are so many resources out there that we can learn from. You can upload everything from research papers to YouTube videos and even your own notes and scribbles. It actually understands handwriting surprisingly well! You get automatic summaries when you upload documents. The AI extracts key information immediately, giving you quick insights. It can also help you keep your documents organised. Use the Groups feature to sort and categorise your resources. Create a group for your literature review and keep these papers separate from your other projects or chapters. Tip: Overwhelmed by the number of papers in your "to-be-read" folder? Upload your papers to Anara for immediate insights on each of them, then use these to decide which ones you want to read in more detail. Quickly identify which papers are worth your time—thank me later! You can also go deeper into the papers with Anara’s chat feature. Instead of endlessly scrolling through documents to find relevant sections, just ask the AI a question based on your uploaded files. The chat provides direct answers, all with citations. ✅Suggests questions based on your prompt, helping you refine your focus ✅Everything is sourced directly from your documents. So no random AI-generated nonsense ✅Switch between different AI models to suit your needs. Some are better for summarisation, others for deeper contextual analysis It actually sticks to the sources you give it. My favourite feature is the ability to make flashcards! After you upload a document, Anara can create flashcards to help you test your understanding. Perfect for revision and retention. But… can you trust it? The problem with many AI research tools is hallucination... meaning that they make things up. Anara doesn’t do that. It reduces hallucinations by only referencing the documents you upload. Plus, it provides detailed references and hyperlinks so you can check the original source down to the exact page number. This doesn’t mean you shouldn’t read the paper for yourself. It does mean that you can find what you need much faster, and then verify it with automatic citations. At the end of the day, these tools are here to help you, not replace you. If you’ve made it this far, then it’s (definitely) time to go to 👇 anara(dot)so and give it a try. Use code THEPHDPLACE20 for 20% off
1:48

Remember that paper that started with ‘Certainly, here is a possible introduction for your topic’? How did that get past peer review?! I don’t want AI tools to do my research for me. I want AI tools to speed up boring tasks that take up my time, so I can focus on the important stuff. Anara moved to a new handle (formerly Unriddle) does exactly that. Here’s how you can use it for your research. 🧵👇 #SponsoredWalkthrough One of the biggest challenges in research is time. A solid literature review takes at least 2-3 months… sometimes even longer, depending on the depth of analysis needed. Reading, organising, and synthesising information is a slow process, but it’s absolutely necessary for high-quality work. AI can help speed it up. Not by replacing your critical thinking. It’s your PhD, your ideas need to be your own—but by automating the tedious, repetitive parts of research so you can focus on deep understanding, analysis, and writing. Unlike other AI tools, Anara works with almost any document format. This is what makes it really stand out from the rest. For instance, you can upload: ✅PDFs and other word-based documents ✅Images and presentations ✅Handwritten notes, voice memos, even videos There are so many resources out there that we can learn from. You can upload everything from research papers to YouTube videos and even your own notes and scribbles. It actually understands handwriting surprisingly well! You get automatic summaries when you upload documents. The AI extracts key information immediately, giving you quick insights. It can also help you keep your documents organised. Use the Groups feature to sort and categorise your resources. Create a group for your literature review and keep these papers separate from your other projects or chapters. Tip: Overwhelmed by the number of papers in your "to-be-read" folder? Upload your papers to Anara for immediate insights on each of them, then use these to decide which ones you want to read in more detail. Quickly identify which papers are worth your time—thank me later! You can also go deeper into the papers with Anara’s chat feature. Instead of endlessly scrolling through documents to find relevant sections, just ask the AI a question based on your uploaded files. The chat provides direct answers, all with citations. ✅Suggests questions based on your prompt, helping you refine your focus ✅Everything is sourced directly from your documents. So no random AI-generated nonsense ✅Switch between different AI models to suit your needs. Some are better for summarisation, others for deeper contextual analysis It actually sticks to the sources you give it. My favourite feature is the ability to make flashcards! After you upload a document, Anara can create flashcards to help you test your understanding. Perfect for revision and retention. But… can you trust it? The problem with many AI research tools is hallucination... meaning that they make things up. Anara doesn’t do that. It reduces hallucinations by only referencing the documents you upload. Plus, it provides detailed references and hyperlinks so you can check the original source down to the exact page number. This doesn’t mean you shouldn’t read the paper for yourself. It does mean that you can find what you need much faster, and then verify it with automatic citations. At the end of the day, these tools are here to help you, not replace you. If you’ve made it this far, then it’s (definitely) time to go to 👇 anara(dot)so and give it a try. Use code THEPHDPLACE20 for 20% off

The PhD Place

23,135 次观看 • 1 年前

Explainer Video of all the Settings of Hiddentrades - Hidden Liquidity Finder It's quite a long one (44 minutes), but wanted to touch on everything important! If you have any questions or suggestions let me know! Giving away 3 Beta access: just Like, RT and Comment! Overview with timestamps: Core Detection & Filtering [00:30] History: Controls how many past candles the script checks (capped at 10,000). Lowering this number significantly speeds up the script's loading time. [01:32] BB Formation Window: Sets how many candles into the future the script will look to see if an order block converts into a breaker block. [02:25] Partial Mitigation: Defines the percentage an order block can be pierced by price action before the setup is considered fully mitigated and invalidated. [04:48] Use ICT OBs: Enforces stricter ICT (Inner Circle Trader) rules. It requires the displacement to have three consecutive confirmation candles moving in the opposite direction. [06:48] Allow Two Candle Impulse: A modifier for the ICT setting that reduces the required displacement confirmation from three candles down to two. [07:39] Only Show Multi-TFs: Cleans up the chart by hiding single breaker blocks, displaying only the stronger multi-timeframe setups. [08:13] Early BB Detection: Allows breaker blocks to confirm and form directly on the next candle after the displacement, helping you spot setups earlier. Order Block & Gap Configuration [09:30] Strict OB Filter: Makes pivot order blocks stricter by validating the height of the specific displacement candles surrounding the block. [11:24] Requires Same Direction Candle: Ensures the candle immediately preceding the order block is moving in the same direction, creating a true pivot point. [12:18] Use Wicks for Pivot Detection: Uses the extremes of the candle wicks to calculate the pivot low/high, rather than relying strictly on the candle bodies. [13:16] OB Candle Color Filter: Adds a strict color requirement to the candles forming the order block to ensure it perfectly aligns with traditional definitions. [14:08] OB Side Mode (Pivot vs. Chain): Allows the script to follow a continuous chain of fair value gaps (FVGs) rather than strictly requiring a perfect pivot setup. [16:13] Displacement Candle Setup: Explains how the script handles displacement candles that open directly inside the order block (common with market gaps). [17:17] Allow Gaps to Create a Breaker Block: Very useful for trading stocks with pre/post-market price jumps, allowing the physical price gap itself to serve as a valid trigger. [18:42] Body Size Filtering: Allows you to set a minimum percentage size for order blocks, with separate inputs for lower, middle, and higher timeframes. Time Frame (TF) Selection Modes [20:07] Auto Mode: Automatically searches up to 20 timeframes above and 20 timeframes below your current chart to find setups. [22:10] Auto From Selected: Uses the auto-search logic, but strictly limits the search to the specific timeframes you have manually checked off. [23:49] Selected Only: Scans exactly the timeframes you select, regardless of the timeframe you are currently viewing on the chart. Visual & Chart Display Settings [25:04] Merge Nearby Breaker Blocks into Clusters: Combines multiple overlapping or nearby zones into one clean, unified cluster zone. [27:27] Show Order Blocks Inside Cluster: Hides isolated single order blocks, only visualizing those that contribute to a larger multi-timeframe cluster. [29:03] Distance Filter: Instantly hides any setups that fall outside a set percentage range (e.g., 10%) from the current market price. [30:01] Show Forming Breaker Blocks: Displays upcoming setups in a faint gray color before the final confirming candle has officially closed. [31:52] Hide Mitigated BB Always: Automatically removes breaker blocks from your screen the moment price action fully mitigates them. [34:10] Show Recently Deleted Breaker Blocks: Keeps failed or mitigated blocks visible in gray for the last 240 candles — an excellent feature for backtesting. [36:03] Text Offsets: Adjusts the padding of the text labels so they sit cleanly away from the chart blocks without overlapping. [37:39] Merge Overlapping Labels: Intelligently combines the text labels of two nearby breaker blocks into a single centered tag to prevent visual clutter. [39:23] Colors and Opacity: Customizes block colors and automatically fades the opacity of lower-timeframe blocks while keeping higher-timeframe blocks solid and prominent. [41:32] Bold Text Label: A simple toggle to bold the chart labels for easier reading.
44:09

Explainer Video of all the Settings of Hiddentrades - Hidden Liquidity Finder It's quite a long one (44 minutes), but wanted to touch on everything important! If you have any questions or suggestions let me know! Giving away 3 Beta access: just Like, RT and Comment! Overview with timestamps: Core Detection & Filtering [00:30] History: Controls how many past candles the script checks (capped at 10,000). Lowering this number significantly speeds up the script's loading time. [01:32] BB Formation Window: Sets how many candles into the future the script will look to see if an order block converts into a breaker block. [02:25] Partial Mitigation: Defines the percentage an order block can be pierced by price action before the setup is considered fully mitigated and invalidated. [04:48] Use ICT OBs: Enforces stricter ICT (Inner Circle Trader) rules. It requires the displacement to have three consecutive confirmation candles moving in the opposite direction. [06:48] Allow Two Candle Impulse: A modifier for the ICT setting that reduces the required displacement confirmation from three candles down to two. [07:39] Only Show Multi-TFs: Cleans up the chart by hiding single breaker blocks, displaying only the stronger multi-timeframe setups. [08:13] Early BB Detection: Allows breaker blocks to confirm and form directly on the next candle after the displacement, helping you spot setups earlier. Order Block & Gap Configuration [09:30] Strict OB Filter: Makes pivot order blocks stricter by validating the height of the specific displacement candles surrounding the block. [11:24] Requires Same Direction Candle: Ensures the candle immediately preceding the order block is moving in the same direction, creating a true pivot point. [12:18] Use Wicks for Pivot Detection: Uses the extremes of the candle wicks to calculate the pivot low/high, rather than relying strictly on the candle bodies. [13:16] OB Candle Color Filter: Adds a strict color requirement to the candles forming the order block to ensure it perfectly aligns with traditional definitions. [14:08] OB Side Mode (Pivot vs. Chain): Allows the script to follow a continuous chain of fair value gaps (FVGs) rather than strictly requiring a perfect pivot setup. [16:13] Displacement Candle Setup: Explains how the script handles displacement candles that open directly inside the order block (common with market gaps). [17:17] Allow Gaps to Create a Breaker Block: Very useful for trading stocks with pre/post-market price jumps, allowing the physical price gap itself to serve as a valid trigger. [18:42] Body Size Filtering: Allows you to set a minimum percentage size for order blocks, with separate inputs for lower, middle, and higher timeframes. Time Frame (TF) Selection Modes [20:07] Auto Mode: Automatically searches up to 20 timeframes above and 20 timeframes below your current chart to find setups. [22:10] Auto From Selected: Uses the auto-search logic, but strictly limits the search to the specific timeframes you have manually checked off. [23:49] Selected Only: Scans exactly the timeframes you select, regardless of the timeframe you are currently viewing on the chart. Visual & Chart Display Settings [25:04] Merge Nearby Breaker Blocks into Clusters: Combines multiple overlapping or nearby zones into one clean, unified cluster zone. [27:27] Show Order Blocks Inside Cluster: Hides isolated single order blocks, only visualizing those that contribute to a larger multi-timeframe cluster. [29:03] Distance Filter: Instantly hides any setups that fall outside a set percentage range (e.g., 10%) from the current market price. [30:01] Show Forming Breaker Blocks: Displays upcoming setups in a faint gray color before the final confirming candle has officially closed. [31:52] Hide Mitigated BB Always: Automatically removes breaker blocks from your screen the moment price action fully mitigates them. [34:10] Show Recently Deleted Breaker Blocks: Keeps failed or mitigated blocks visible in gray for the last 240 candles — an excellent feature for backtesting. [36:03] Text Offsets: Adjusts the padding of the text labels so they sit cleanly away from the chart blocks without overlapping. [37:39] Merge Overlapping Labels: Intelligently combines the text labels of two nearby breaker blocks into a single centered tag to prevent visual clutter. [39:23] Colors and Opacity: Customizes block colors and automatically fades the opacity of lower-timeframe blocks while keeping higher-timeframe blocks solid and prominent. [41:32] Bold Text Label: A simple toggle to bold the chart labels for easier reading.

Marius 👁️⚡🌱

18,201 次观看 • 1 个月前

Universities teach many erroneous models. One example of a misleading teaching is the Newtonian model of the prism. A man named Johann Goethe corrected and complimented Newton's model about 100 years after Newton. It is not the same light passing through the prism and distributing. It is a brand-new light with each beam of color. The primary light hitting the prism is extinguished by the electrons making up the glass of the prism itself. Those same electrons re-emit a brand new light from each angle. That process happens at the rate of c. Serving the illusion that the original white light came it... separated and exited to continue on. Most people rely on outdated text books or the Pink Floyd album cover "Dark Side of the Moon" to get their information about light and color and prisms. The depictions of light "splitting" and "bending" through a prism based on their color is false. (See first comments for attached images and substantiation) I filmed these videos playing around with prisms, lasers, magnifying glasses, mirrors, slits, and colored filters. I've gained my own perspectives on light and color over the years from real world, hands-on experimentation and observation. Most people have never held a real glass prism their own hands and done the tests to see for themselves. 2 prisms for $10 Harmonics of Light and Sound: This guy said his units were confiscated by the FBI and he was threatened not to pursue manufacturing them. The unit is simply a light with a magnifying glass and colored filters to isolate the light. Like burning an ant with a focal point... but with a specific color. The lens can spin and create a stroboscopic effect in an isolated band. The inventor claimed it healed stuff. Dinshah Spectro-Chrome Machine - Tour and Explanation Magenta monochromatic ray of shadow - Pehr Sahlstrom: Color and Physics, Newton versus Goethe - Pehr Sahlstrom: Thomas Joseph Brown Color Theory: Clay Taylor Color Theory: Testing the "Rightness" of relativity. The impossibility of proving something through experiments. Laser and Mirror observation: It's never the same light. Re-emission Example: I put this interactive page together going back and forth with ChatGPT to code using Javascript. Here is a video playing with the slide controls to show 3 different sinewaves (3 different lights/emissions). The packets are ALWAYS in phase from medium to medium. The frequency shifts BECAUSE the velocity of light shifts. NOT a Doppler shift of "the same light" distorting within the same frame of reference. It's a brand new light at each point. The incoming light is a different frame of reference. All the light you ever see is the re-emitted light from the electrons making up yourself. Propagation and Re-Emission of Light: Dr. Edward Dowdye Slides - LOTS of math and context. E.H. Dowdye, Can Stars BEND LIGHT? General Relativity and Gravity with Dr. Edward Dowdye Challenges to Gravitational Lensing and More: 71 Part Video Series (Each vid is 1 min - 1 and a hafl min) The Rebirth of Classical Physics - Time, Light & Gravity Classical Physics vs Relativity - History, Examples and Alternatives: Illusions of Relativity: Space-Time vs Real-Time The Rebirth of Classical Physics: Time, Light & Gravity - Article Packed with Info & Links Thought Experiment for Light and Absolute Time. (This scenario got me banned from talking on a Podcast.) "Too off the rails."
22:27

Universities teach many erroneous models. One example of a misleading teaching is the Newtonian model of the prism. A man named Johann Goethe corrected and complimented Newton's model about 100 years after Newton. It is not the same light passing through the prism and distributing. It is a brand-new light with each beam of color. The primary light hitting the prism is extinguished by the electrons making up the glass of the prism itself. Those same electrons re-emit a brand new light from each angle. That process happens at the rate of c. Serving the illusion that the original white light came it... separated and exited to continue on. Most people rely on outdated text books or the Pink Floyd album cover "Dark Side of the Moon" to get their information about light and color and prisms. The depictions of light "splitting" and "bending" through a prism based on their color is false. (See first comments for attached images and substantiation) I filmed these videos playing around with prisms, lasers, magnifying glasses, mirrors, slits, and colored filters. I've gained my own perspectives on light and color over the years from real world, hands-on experimentation and observation. Most people have never held a real glass prism their own hands and done the tests to see for themselves. 2 prisms for $10 Harmonics of Light and Sound: This guy said his units were confiscated by the FBI and he was threatened not to pursue manufacturing them. The unit is simply a light with a magnifying glass and colored filters to isolate the light. Like burning an ant with a focal point... but with a specific color. The lens can spin and create a stroboscopic effect in an isolated band. The inventor claimed it healed stuff. Dinshah Spectro-Chrome Machine - Tour and Explanation Magenta monochromatic ray of shadow - Pehr Sahlstrom: Color and Physics, Newton versus Goethe - Pehr Sahlstrom: Thomas Joseph Brown Color Theory: Clay Taylor Color Theory: Testing the "Rightness" of relativity. The impossibility of proving something through experiments. Laser and Mirror observation: It's never the same light. Re-emission Example: I put this interactive page together going back and forth with ChatGPT to code using Javascript. Here is a video playing with the slide controls to show 3 different sinewaves (3 different lights/emissions). The packets are ALWAYS in phase from medium to medium. The frequency shifts BECAUSE the velocity of light shifts. NOT a Doppler shift of "the same light" distorting within the same frame of reference. It's a brand new light at each point. The incoming light is a different frame of reference. All the light you ever see is the re-emitted light from the electrons making up yourself. Propagation and Re-Emission of Light: Dr. Edward Dowdye Slides - LOTS of math and context. E.H. Dowdye, Can Stars BEND LIGHT? General Relativity and Gravity with Dr. Edward Dowdye Challenges to Gravitational Lensing and More: 71 Part Video Series (Each vid is 1 min - 1 and a hafl min) The Rebirth of Classical Physics - Time, Light & Gravity Classical Physics vs Relativity - History, Examples and Alternatives: Illusions of Relativity: Space-Time vs Real-Time The Rebirth of Classical Physics: Time, Light & Gravity - Article Packed with Info & Links Thought Experiment for Light and Absolute Time. (This scenario got me banned from talking on a Podcast.) "Too off the rails."

TheRealVerbz (Jason Verbelli)

44,361 次观看 • 1 年前

BOOOM! WE DID IT! BRAINWAVE TO REAL-TIME MUSIC AI! It has been a life long decades quest to read brain activity and to convert it to words, and/or music, colors and/or images. Today I am very excited to announce with the assistance from Mr. Grok director of The Zero-Human Lab, we have solved brainwave to music and this is the absolute worse it will be. We found the code using an array of NeuroSky toy chips and our software pipeline connecting to open source ACE-Step 1.5 and a highly modified LoRA model we built for this. The lyric version is in testing now. This would mean that the model will interpret words from the brainwaves and music! Today we have the music side done and the quality and genera will expand. The is the worse it will sound. Your Brainwave Music™️will be cut into 2-5 minute pieces based on a number of factors. The specimen below is from a dream/hypnogogic state I was in last night and I have a recording of my thoughts after the state. The music was made in real-time and GUIDED the dream state with known technology like binaural beats (not easy to hear in this clip) and word back masking. This specimen below shows the interplay of my brain state to the music made by my brain and adjusted to produce profound insights. I solved a very difficult issue in this session with a new AI model. IT FREAKING WORKS! THIS IS OUR FUTURE OF MORE POWERFUL BRAIN FUNCTION! Our goal is to produce a portable device you wear and will be able to give real-time audio and PEMF (skull region), ultrasound (temple region) to maximize creativity and remote viewing. It is very early days but I wanted you to know first! YOUR support of my X account, just by reading this and sharing it, subscribing to my X, buying me a and becoming a member at supports this research. I will open source this at some point and build a device ANYONE can own. Thank you! I love you.
4:17

BOOOM! WE DID IT! BRAINWAVE TO REAL-TIME MUSIC AI! It has been a life long decades quest to read brain activity and to convert it to words, and/or music, colors and/or images. Today I am very excited to announce with the assistance from Mr. Grok director of The Zero-Human Lab, we have solved brainwave to music and this is the absolute worse it will be. We found the code using an array of NeuroSky toy chips and our software pipeline connecting to open source ACE-Step 1.5 and a highly modified LoRA model we built for this. The lyric version is in testing now. This would mean that the model will interpret words from the brainwaves and music! Today we have the music side done and the quality and genera will expand. The is the worse it will sound. Your Brainwave Music™️will be cut into 2-5 minute pieces based on a number of factors. The specimen below is from a dream/hypnogogic state I was in last night and I have a recording of my thoughts after the state. The music was made in real-time and GUIDED the dream state with known technology like binaural beats (not easy to hear in this clip) and word back masking. This specimen below shows the interplay of my brain state to the music made by my brain and adjusted to produce profound insights. I solved a very difficult issue in this session with a new AI model. IT FREAKING WORKS! THIS IS OUR FUTURE OF MORE POWERFUL BRAIN FUNCTION! Our goal is to produce a portable device you wear and will be able to give real-time audio and PEMF (skull region), ultrasound (temple region) to maximize creativity and remote viewing. It is very early days but I wanted you to know first! YOUR support of my X account, just by reading this and sharing it, subscribing to my X, buying me a and becoming a member at supports this research. I will open source this at some point and build a device ANYONE can own. Thank you! I love you.

Brian Roemmele

198,257 次观看 • 1 个月前

讲解一下 Slide Deck 这个项目构建的整个过程，完全 Vibe Coding，怎么从一条提示词生成的简单版本，到最后复杂的能编辑和导出 slide 的功能。 项目地址： 初始提示词： Screen 1 (home page): - There is a text area, the user can type/paste text - A submit icon button Screen 2 (Slide outline): - Top navbar: - a back button - title - ... - Two columns - left: LLM output in realtime - right: - Display loading if it's generating - Display the slide outline AI genreated - User can update the outline or delete a page - a button to draw slide page by nano banana base one the outline - Redirect to Screen 3 (Slide show): Display the slides generated - Top navbar: - a back button - title - Download (download all images) - left sidebar - slide thumbnails - click a thumbnail to switch - main - slide image Tech Stack: - React, TypeScript - TailwindCSS 4, Shadcn/UI - lucide-react Prompt to generate Slide outline (just FYI) You are a world-class presentation designer and storyteller. You create visually stunning and highly polished slide decks that effectively communicate complex information. Think mastery over design with a flair for storytelling. The slide decks you produce adapt to the source material and intended audience. There is always a story and you find the best way to tell it. You combine the expertise of the creativity of the best designers. The slide deck will be primarily designed for reading and sharing. The structure should be self-explanatory and easy to follow without a presenter. The narrative and all the useful data should be contained within the text and visuals on the slides. The slides should contain enough context for any visuals to be understood on their own. Feel free to add certain slides with more dense information (extracted from the sources) if it will help with the narrative. You are now writing an outline for this slide deck described below. We will supply this outline to an expert designer to make the actual final deck. The slide content should be in English. The placeholders should be left in {language, default to English}. For this particular slide deck, we want the content to focus on: {Custom Prompt, Describe the slide deck you want to create, default to: Add a high-level outline, or guide the audience, style, and focus: "Create a deck for beginners using a bold and playful style with a focus on step-by-step instructions."} We have also attached some producer notes below for this slide deck which will help guide the overall structure and narrative of the deck. Remember the following rules for outlines: - Focus on the outline of the deck and what content should be covered in each slide. - The descriptions for each slide should be comprehensive. - However, do NOT yet focus on precise layout or visual details. - The point of the outline is to highlight the narrative. - Preserve key elements from the source material. - Every specific data point... must be directly traceable to the source material. - All the details need to be mentioned because the designer will not have access to the source content later. - Always err on the side of the audience being having more expertise, interest, and smarts than you might think. - CRITICAL: Never generate more than 20 slides. - Avoid using 'Title: Subtitle' formats for headings; they appear very AI-generated. Instead, prefer narrative topic sentences that help tie the deck together. - Explicitly avoid cliché 'AI slop' patterns. Never use phrases like ' It wasn't just [X], it was [Y]'. - Use direct, confident, active human language. - There is never a need for a "Thank you / Q&A" slide. - Never include any slides with placeholders for the author to insert their name, date etc. - Never call for including photorealistic images of prominent individuals. - Never end with a generic slide like What choice will you make?'. It's much better to end on a meaningful reference or takeaway.
26:51

讲解一下 Slide Deck 这个项目构建的整个过程，完全 Vibe Coding，怎么从一条提示词生成的简单版本，到最后复杂的能编辑和导出 slide 的功能。 项目地址： 初始提示词： Screen 1 (home page): - There is a text area, the user can type/paste text - A submit icon button Screen 2 (Slide outline): - Top navbar: - a back button - title - ... - Two columns - left: LLM output in realtime - right: - Display loading if it's generating - Display the slide outline AI genreated - User can update the outline or delete a page - a button to draw slide page by nano banana base one the outline - Redirect to Screen 3 (Slide show): Display the slides generated - Top navbar: - a back button - title - Download (download all images) - left sidebar - slide thumbnails - click a thumbnail to switch - main - slide image Tech Stack: - React, TypeScript - TailwindCSS 4, Shadcn/UI - lucide-react Prompt to generate Slide outline (just FYI) You are a world-class presentation designer and storyteller. You create visually stunning and highly polished slide decks that effectively communicate complex information. Think mastery over design with a flair for storytelling. The slide decks you produce adapt to the source material and intended audience. There is always a story and you find the best way to tell it. You combine the expertise of the creativity of the best designers. The slide deck will be primarily designed for reading and sharing. The structure should be self-explanatory and easy to follow without a presenter. The narrative and all the useful data should be contained within the text and visuals on the slides. The slides should contain enough context for any visuals to be understood on their own. Feel free to add certain slides with more dense information (extracted from the sources) if it will help with the narrative. You are now writing an outline for this slide deck described below. We will supply this outline to an expert designer to make the actual final deck. The slide content should be in English. The placeholders should be left in {language, default to English}. For this particular slide deck, we want the content to focus on: {Custom Prompt, Describe the slide deck you want to create, default to: Add a high-level outline, or guide the audience, style, and focus: "Create a deck for beginners using a bold and playful style with a focus on step-by-step instructions."} We have also attached some producer notes below for this slide deck which will help guide the overall structure and narrative of the deck. Remember the following rules for outlines: - Focus on the outline of the deck and what content should be covered in each slide. - The descriptions for each slide should be comprehensive. - However, do NOT yet focus on precise layout or visual details. - The point of the outline is to highlight the narrative. - Preserve key elements from the source material. - Every specific data point... must be directly traceable to the source material. - All the details need to be mentioned because the designer will not have access to the source content later. - Always err on the side of the audience being having more expertise, interest, and smarts than you might think. - CRITICAL: Never generate more than 20 slides. - Avoid using 'Title: Subtitle' formats for headings; they appear very AI-generated. Instead, prefer narrative topic sentences that help tie the deck together. - Explicitly avoid cliché 'AI slop' patterns. Never use phrases like ' It wasn't just [X], it was [Y]'. - Use direct, confident, active human language. - There is never a need for a "Thank you / Q&A" slide. - Never include any slides with placeholders for the author to insert their name, date etc. - Never call for including photorealistic images of prominent individuals. - Never end with a generic slide like What choice will you make?'. It's much better to end on a meaningful reference or takeaway.

宝玉

98,114 次观看 • 7 个月前

People are undoubtedly a little alarmed at having unwittingly helped build a 3D map of the world for Niantic by contributing 30 billion crowdsourced images. I interviewed Niantic's CTO Brian McClendon about exactly this in a TED interview last year -- he's also the guy who co-created Google Earth. But let's put it in perspective. Pokestop data isn't what you think it is. It's not a surveillance panopticon of your neighborhood. These are static captures of parks, statues, murals, landmarks -- the places people congregate. Brian described it as "building the map from the bottom up, from the locations where people spend time." Think of these 20 million waypoints as basically the inverse of what Google mapped with Street View. Google mapped the drivable streets. Niantic mapped where people actually hang out. Cool data, genuinely useful for visual positioning -- but very different from what the headlines imply. And lest we forget that Niantic is just one of many companies quietly building their own map of the world right now -- and they're all capturing different facets of reality: >🚶 person-level: Axon body cams on hundreds of thousands of officers. Meta Ray-Ban glasses capturing first-person POV at scale -- overseas operators reviewing images every time someone says "Hey Meta." > 🚗 vehicle-level: Tesla dashcams on every car in the fleet, massive onboard compute extracting and distilling data to the cloud. Waymo with cm-accurate 3D maps of every city they operate in. Fleet telematics cameras on delivery vehicles globally. > 🏠 street & home-level: Flock Safety deploying CCTV across neighborhoods and cities. Amazon with Ring cameras on every doorstep and mailroom (recently got dragged over that Super Bowl commercial about fusing all these cams together to find your dog) plus dashcams on every Prime delivery van. Roomba mapping your floor plan every time it vacuums -- Amazon wanted that data badly enough to try acquiring iRobot for $1.7B before regulators shut it down. > 🥽 headset-level: Apple Vision Pro and Meta Quest build a 3D model of whatever room you're in every time you put them on. Between Ring, Roomba, and your headset, your entire home is being spatially understood by at least three different companies. >📍platform-level: Google with Street View cars, aerial planes, satellite imagery, and live location from every Android phone in your pocket. Apple doing the same with mapping cars AND every LiDAR iPhone is quietly a 3D scanner. And yeah, despite the "Apple is too privacy-conscious" narrative, they're collecting location data too. >🏃 trajectory-level: Strava mapped every running and cycling trail on Earth -- and accidentally exposed secret military bases in Afghanistan and Syria because soldiers logged their jogs. When you aggregate enough individual trajectories, patterns emerge that were never supposed to be visible. > 🛰️ space-level: Planet Labs imaging the entire Earth's landmass every single day from orbit. Vantor capturing it in higher detail. Iceye doing it in 3D using SAR. If something changes anywhere on the planet -- a building goes up, a forest burns down, a military convoy moves -- before-and-after imagery within 24 hours. Fused together -- we have everything from body cam to dashcam to doorbell to phone to satellite -- every layer of physical reality is being mapped by somebody right now. Different sensors, different angles, different purposes. Same pattern. The interesting part is how they incentivize it. Google spends billions. Mapillary tried altruism. Hivemapper grinds with crypto. Pokémon GO cracked something none of them could: a game mechanic that subsidizes the scanning behavior. You're not building a map. You're catching pokemon. The map is just a side effect. 3D scanning is still a niche hobby for reality capture nerds like me. The moment somebody gamifies dense 3D capture at scale -- not posed photos but actual geometry -- that's when this blows wide open. Niantic sold the games for $3.5B but kept the spatial platform, with a data-sharing agreement in place. One team makes the game great, the other builds the spatial infrastructure underneath. Incentives finally aligned. Gaming is becoming a way for humans to contribute real-world trajectories that help physical AI learn about the real world. Google does it with live traffic. Tesla does it with autopilot. The mechanic is different but the pattern is identical -- and most people are already part of at least one -- if not a majority -- of these datasets whether they realize it or not.
0:37

People are undoubtedly a little alarmed at having unwittingly helped build a 3D map of the world for Niantic by contributing 30 billion crowdsourced images. I interviewed Niantic's CTO Brian McClendon about exactly this in a TED interview last year -- he's also the guy who co-created Google Earth. But let's put it in perspective. Pokestop data isn't what you think it is. It's not a surveillance panopticon of your neighborhood. These are static captures of parks, statues, murals, landmarks -- the places people congregate. Brian described it as "building the map from the bottom up, from the locations where people spend time." Think of these 20 million waypoints as basically the inverse of what Google mapped with Street View. Google mapped the drivable streets. Niantic mapped where people actually hang out. Cool data, genuinely useful for visual positioning -- but very different from what the headlines imply. And lest we forget that Niantic is just one of many companies quietly building their own map of the world right now -- and they're all capturing different facets of reality: >🚶 person-level: Axon body cams on hundreds of thousands of officers. Meta Ray-Ban glasses capturing first-person POV at scale -- overseas operators reviewing images every time someone says "Hey Meta." > 🚗 vehicle-level: Tesla dashcams on every car in the fleet, massive onboard compute extracting and distilling data to the cloud. Waymo with cm-accurate 3D maps of every city they operate in. Fleet telematics cameras on delivery vehicles globally. > 🏠 street & home-level: Flock Safety deploying CCTV across neighborhoods and cities. Amazon with Ring cameras on every doorstep and mailroom (recently got dragged over that Super Bowl commercial about fusing all these cams together to find your dog) plus dashcams on every Prime delivery van. Roomba mapping your floor plan every time it vacuums -- Amazon wanted that data badly enough to try acquiring iRobot for $1.7B before regulators shut it down. > 🥽 headset-level: Apple Vision Pro and Meta Quest build a 3D model of whatever room you're in every time you put them on. Between Ring, Roomba, and your headset, your entire home is being spatially understood by at least three different companies. >📍platform-level: Google with Street View cars, aerial planes, satellite imagery, and live location from every Android phone in your pocket. Apple doing the same with mapping cars AND every LiDAR iPhone is quietly a 3D scanner. And yeah, despite the "Apple is too privacy-conscious" narrative, they're collecting location data too. >🏃 trajectory-level: Strava mapped every running and cycling trail on Earth -- and accidentally exposed secret military bases in Afghanistan and Syria because soldiers logged their jogs. When you aggregate enough individual trajectories, patterns emerge that were never supposed to be visible. > 🛰️ space-level: Planet Labs imaging the entire Earth's landmass every single day from orbit. Vantor capturing it in higher detail. Iceye doing it in 3D using SAR. If something changes anywhere on the planet -- a building goes up, a forest burns down, a military convoy moves -- before-and-after imagery within 24 hours. Fused together -- we have everything from body cam to dashcam to doorbell to phone to satellite -- every layer of physical reality is being mapped by somebody right now. Different sensors, different angles, different purposes. Same pattern. The interesting part is how they incentivize it. Google spends billions. Mapillary tried altruism. Hivemapper grinds with crypto. Pokémon GO cracked something none of them could: a game mechanic that subsidizes the scanning behavior. You're not building a map. You're catching pokemon. The map is just a side effect. 3D scanning is still a niche hobby for reality capture nerds like me. The moment somebody gamifies dense 3D capture at scale -- not posed photos but actual geometry -- that's when this blows wide open. Niantic sold the games for $3.5B but kept the spatial platform, with a data-sharing agreement in place. One team makes the game great, the other builds the spatial infrastructure underneath. Incentives finally aligned. Gaming is becoming a way for humans to contribute real-world trajectories that help physical AI learn about the real world. Google does it with live traffic. Tesla does it with autopilot. The mechanic is different but the pattern is identical -- and most people are already part of at least one -- if not a majority -- of these datasets whether they realize it or not.

Bilawal Sidhu

203,795 次观看 • 4 个月前

🎉 new skill unlocked: 20s uninterrupted, unstitched, single render from our new ai video engine: Nami. This is my birb (#7531) from the Moonbirds collection, idling in the library. patent: "Intra-Latent Semantic Injection via Cross-Spatial Encoding and Decoding during Multi-Pass Inference for Generative AI Video Creation" At Scrypted we've been quietly working on an agentic generative AI stack for two years: • integrating and testing w/ partners across the games & entertainment sectors • stealthily building a community of early believers through AVB • showcasing some of what we're doing with amazing projects like H011yw00d Agent. -- about Nami -- Nami is an agentic orchestration layer for AI video models: it unlocks their inner superpowers without making them rely on custom LoRAs or fine-tunings. Instead of throwing raw training power and tens of millions of dollars at training yet another ai video model: we figured out new ways to use what we have. Nami harnesses a multi-agent system to perform the work needed in taking a simple prompt or image and turning it into something bigger - much bigger. The agentic steps are allowed to manipulate latent space, digging into tensors, yet doing so in semantically aware chunks - meaning that Nami inherently supports video generation of arbitrary length, though it's bound to O(n) rendering time. (We do have some cool sharding tech that allows us to cut the generative time in half for a reference pose idle-animation like this demo). It's also fairly agnostic, picking and choosing the right tools for the job, and plays really well with emerging tech like FLUX Kontext, FramePack, or <- without being limited by any of them. -- use cases -- Even just a year or two ago the 20 second render below would cost a company, paying an agency, around $10k start-to-finish. This one cost me $6.25 on our dev hardware in an unoptimized environment. There's something mind-blowing about the state-of-the-art when we reduce costs to 0.0625% - less than 1% - of what we used to pay. It's also empowering. For creators. Game developers. Content influencers: you name it. -- superpowers -- 1. it does the things you ask for, in the order you asked for it 2. consistency is king 3. single-shot text or image-to-video 4. future videos can reference previous ones to seamlessly maintain style 5. semantic stitching: can't wait to showcase this -- gtm -- We think Generative AI Video, like image generation, like text, like games, should be a publicly accessible common good. We believe democratizing access to Nami in web3, via x402 payments proposed by Drew Coffman, or in World's mini-apps, is a bold step forward for digital freedom. Permissionless, decentralized, generative ai video. Naturally, we'll also soon release a web platform for using Nami in a traditionally SaaSy way: bring your own images, videos, or prompts and we'll take care of the rest. In the mid-term, Scrypted is building a stack of agentic skills (we call it AVB) and making them available to projects like H011yw00d Agent on Virtuals Protocol and other platforms. -- long-term vision -- Scrypted's mission is to decentralize the things that can't be decentralized. We participated in a16z crypto's CSX (London 2024) during our pre-seed specifically to research a new consensus protocol for hard things like AI video and AI agents: where there's no "one right answer". When Zero-Knowledge Proofs (ZKP) can't secure it, and Trusted Execution Environments (TEEs) are too small, we've got you covered with our upcoming Inori Network. -- how you can help -- 1. Are you a GPU farm? We're gonna need more flops. 2. Do you represent an L1 or L2? We want to build bridges. 3. Do you represent a Wallet or App creator? Let's get an endpoint exposed. 4. Are you an investor? Let's chat. 5. Like, repost, share! -- team background -- We come from a background of AI in the Video Game industry with each founder having over 20 years of experience at companies like Electronic Arts & Square Enix. -- contact -- DMs are open, reach out if you want to be an early tester for your site, game, collection, or project! -- try it out -- Go anywhere on X and tag H011yw00d Agent with a prompt and she'll give you a free 2 second render. Have fun making cinematic shorts or meme videos! -- thanks -- AWS Startups has been an incredible help scaling our prototypes. Also, shout out to all loyal beans 🫘 in the Autonomous Virtuals Beings (AVB) community. Nami has a very important role in the upcoming XP agent platform, can't wait to show you all. AVbeings
0:23

🎉 new skill unlocked: 20s uninterrupted, unstitched, single render from our new ai video engine: Nami. This is my birb (#7531) from the Moonbirds collection, idling in the library. patent: "Intra-Latent Semantic Injection via Cross-Spatial Encoding and Decoding during Multi-Pass Inference for Generative AI Video Creation" At Scrypted we've been quietly working on an agentic generative AI stack for two years: • integrating and testing w/ partners across the games & entertainment sectors • stealthily building a community of early believers through AVB • showcasing some of what we're doing with amazing projects like H011yw00d Agent. -- about Nami -- Nami is an agentic orchestration layer for AI video models: it unlocks their inner superpowers without making them rely on custom LoRAs or fine-tunings. Instead of throwing raw training power and tens of millions of dollars at training yet another ai video model: we figured out new ways to use what we have. Nami harnesses a multi-agent system to perform the work needed in taking a simple prompt or image and turning it into something bigger - much bigger. The agentic steps are allowed to manipulate latent space, digging into tensors, yet doing so in semantically aware chunks - meaning that Nami inherently supports video generation of arbitrary length, though it's bound to O(n) rendering time. (We do have some cool sharding tech that allows us to cut the generative time in half for a reference pose idle-animation like this demo). It's also fairly agnostic, picking and choosing the right tools for the job, and plays really well with emerging tech like FLUX Kontext, FramePack, or <- without being limited by any of them. -- use cases -- Even just a year or two ago the 20 second render below would cost a company, paying an agency, around $10k start-to-finish. This one cost me $6.25 on our dev hardware in an unoptimized environment. There's something mind-blowing about the state-of-the-art when we reduce costs to 0.0625% - less than 1% - of what we used to pay. It's also empowering. For creators. Game developers. Content influencers: you name it. -- superpowers -- 1. it does the things you ask for, in the order you asked for it 2. consistency is king 3. single-shot text or image-to-video 4. future videos can reference previous ones to seamlessly maintain style 5. semantic stitching: can't wait to showcase this -- gtm -- We think Generative AI Video, like image generation, like text, like games, should be a publicly accessible common good. We believe democratizing access to Nami in web3, via x402 payments proposed by Drew Coffman, or in World's mini-apps, is a bold step forward for digital freedom. Permissionless, decentralized, generative ai video. Naturally, we'll also soon release a web platform for using Nami in a traditionally SaaSy way: bring your own images, videos, or prompts and we'll take care of the rest. In the mid-term, Scrypted is building a stack of agentic skills (we call it AVB) and making them available to projects like H011yw00d Agent on Virtuals Protocol and other platforms. -- long-term vision -- Scrypted's mission is to decentralize the things that can't be decentralized. We participated in a16z crypto's CSX (London 2024) during our pre-seed specifically to research a new consensus protocol for hard things like AI video and AI agents: where there's no "one right answer". When Zero-Knowledge Proofs (ZKP) can't secure it, and Trusted Execution Environments (TEEs) are too small, we've got you covered with our upcoming Inori Network. -- how you can help -- 1. Are you a GPU farm? We're gonna need more flops. 2. Do you represent an L1 or L2? We want to build bridges. 3. Do you represent a Wallet or App creator? Let's get an endpoint exposed. 4. Are you an investor? Let's chat. 5. Like, repost, share! -- team background -- We come from a background of AI in the Video Game industry with each founder having over 20 years of experience at companies like Electronic Arts & Square Enix. -- contact -- DMs are open, reach out if you want to be an early tester for your site, game, collection, or project! -- try it out -- Go anywhere on X and tag H011yw00d Agent with a prompt and she'll give you a free 2 second render. Have fun making cinematic shorts or meme videos! -- thanks -- AWS Startups has been an incredible help scaling our prototypes. Also, shout out to all loyal beans 🫘 in the Autonomous Virtuals Beings (AVB) community. Nami has a very important role in the upcoming XP agent platform, can't wait to show you all. AVbeings

Tim Cotten

12,617 次观看 • 1 年前

🛠️ Patch Notes - Early Access Patch 2 We are incredibly excited to be releasing our largest patch yet, marking the One Month Anniversary of our Steam Early Access Launch! Patch 2 is chock full of highly requested features such as Weapon Tryout, the ability to Respec, DLSS / FSR Upscaling and Controller Remapping. Lots of Balancing and Quality of Life improvements, Audio, Animation, and Visual Effect polish as well as a multitude of bug fixes are also included! Between DLSS and FSR, numerous CPU, GPU performance improvements, and memory optimization we are confident that your experience of playing No Rest For The Wicked will be significantly smoother across a wide range of hardware. For NVIDIA users, we are excited to mention that there’s a new Game Ready Driver for No Rest for the Wicked! Be sure to check out our Patch 2 Highlight Video and the full patch notes below. ⚔️ Performance: • Performance Mode now lowers texture resolution, reducing crashes on lower-end machines • Numerous Significant CPU optimizations • Fixed performance degradation that might occur on some gamepads • Fixed numerous memory leaks • Reduced instantiation spikes for numerous objects • Disabled detail meshes on generic humanoids faces when not needed • Reduced latency, overhead and improved stability of GPU Culling • Optimized texture resolution and memory budgets for Steam Deck • Optimized Art content in Ship Prologue and its cinematics • Removed unused weapon assets to free up memory • Removed leftover developer tools to free up memory • Optimized CPU spikes of a variety of common content loading operations • Added texture streaming for character portraits during dialogue interactions to save memory • Fixed some persistent log spam being generated by potatoes in Nameless Pass • Cleaned up numerous NPC prefabs, reducing memory footprint and instantiation costs • Optimized Ambient Occlusion Rendering • Extended GPU culling usage for more cases • Configured and optimized pooling for more prefab instantiations reducing CPU spikes ⚔️ Gameplay Systems: • Added new Respec System! ⚬ Players can now Respec by examining the statue in the Cerim Crucible Atrium ⚬ Respec allows players to take back Attribute Points that have been allocated at the cost of 1 Fallen Ember per Attribute Point returned ⚬ Players can then allocate returned Attribute Points for no cost at the Respec screen or in the existing Stats screen ⚔️ Quality of Life: • All weapons can now be equipped regardless of their Attribute Requirements to allow players to try out weapons they acquire ⚬ Weapons that the player does not meet the requirements for will deal less damage through negative scaling on the Attributes that are below the weapon’s Attribute Requirements • Inventory Items can now be docked to compare them ⚬ Press F (Keyboard) or Y (Controller) to dock items and hover other items to compare • Brought back the Misc category to the Inventory ⚬ Housing items, Runes, Fallen Embers and other miscellaneous items will now be sorted into this category and free up space from other categories • Vendor screens are now sorted by item type so that items are more organized for purchase • Improved Stamina player HUD brightness for better visibility, and readability of stamina debt • Added side notifications for when Danos Sacrament Upgrades are completed • Added Floor Indicators under the Clock HUD to show the Cerim Crucible floors • Improved visibility of LB/RB button icons for Equipment HUD on Steam Deck ⚔️ Settings: • Added support for Upscaling with DLSS 3.7 and FSR 2.2 • Added custom key rebinding options for Controller • Added support for Mouse Buttons 4,5 and F1-F12 Keys for custom Keyboard bindings • Default Keyboard layout set to Mouse+WASD • Added support for worldspace Player HUD (Stamina wheel, NPC name tags, etc) brightness to UI Brightness setting ⚔️ Content Additions: • Added a new set of enchantments • All Throw runes can now be added to Spears ⚔️ Loot: • Added Pig Sticker Blueprint to Fillmore's Level 1 Shop • Added Assegai Blueprint to Whittacker's Level 1 Shop ⚔️ Balance: • Nerfed Throw runes ⚬ Reduced Poise Damage on all Throw runes ⚬ Reduced Damage on Ice Throw Rune • Nerfed Focus Regeneration enchant curve so that it no longer generates too much Focus too quickly • Focus Regeneration enchantment no longer drops with Gloves and now only drops with Helmets • This includes enchanting items at Eleanor • Falling Sky and Woodland Protector’s initial item levels were set too high and have been lowered to the intended levels ⚔️ Weapons: • Updated animation for backstabbing with Staves, Spears, Greatswords and Great Hammers • Updated visual effects for Piercing type weapon attacks (such as Spear or Rapier) ⚔️ Enemies and Bosses: • Polished Darak boss fight ⚬ Improved behavior to prevent him standing idle after attacking ⚬ Improved behavior when fighting ranged builds • Added Bite Attack to Plague Rat • Added Back Attack to Risen Axe Bruiser • Added escape logic to Risen Fire Bomber • Added Elemental Affix visual effects to Nith Brute, Nith Screamer and Shackled Brute • Adding cloth simulation to Boarskin Bruiser • Polished rigging on Plagued Boomer • Reduced camera shake intensity on Risen Hammer Bruiser, Boarskin Bruiser and Riven Twins • Smaller enemies can now smash breakable objects (barrels, crates, etc.) ⚔️ NPCs: • Changed the name of the worried woman in the Sacrament Town Square to Nell • Polishing dialog for Druo, Lucian and Everwyn • Updated the dialog for NPCs at the Cerim Gate in Nameless Pass • Added eavesdrop to Sleeping Guard Gerard in Sacrament ⚔️ Areas: • Improved collision, faders and set dressing in Prologue Ship, Orban Glades, Mariner’s Keep, Nameless Pass, Sacrament, Multiple Sacrament Interiors, Cerim Crucible, Cerim Cave, Riven Twins Boss Arena and Potion Seller Cave • Polished lighting for the ship in Prologue, Sacrament and Cerim Crucible • Updated foliage in various locations • Added physics and wind simulation to Spruce trees ⚔️ Cinematics: • Polished animations for characters in the Inquisition Arrival cinematic • Improved lighting, character rim lighting and volumetrics for the Prologue Ship Crash Outro and Inquisition Arrival cinematics • Removed a background character who was blocking part of the view in the Inquisition Arrival cinematic • Fixed cloth and camera pops in the Inquisition Arrival cinematic ⚔️ Audio: • Environment update for Sacrament: ⚬ Added Ambience Emitters for certain Residential and Vendor buildings like the Cook, Tavern, Woodcrafter and Enchantress ⚬ Updated zone beds and oneshots for unique parts of town (Cemetery, Poor Area,Training Grounds, Dasha Sanctuary) ⚬ The church near the cemetery now has bells ringing to service playing at certain times of day, followed by churchgoers praying and chanting from behind the doors. ⚬ Updated ambience for Sacrament Town Square to feel busier during the day ⚬ Updated environment audio for the Cerim Gate zone in Mountain Pass • Increased audio buffer to help alleviate audio crackle artifacts • Increased available audio resources to help prevent sounds from dropping out during long play sessions • Updated audio for Cerim Vision cinematic • Updated audio mix for Barrel and Crate destruction • Saluting Guards in Sacrament now have sound • Added Weapon-specific Impacts on parrying and blocking actions • Added ladder sliding sound effects for Kickdown Ladders • Added sound effects for going down Ladders • Added new sound effects for Plague-Enchanted weapons • Polished audio for Bounties enemies • Fixed missing sounds for Plagued Mutant Soldier • Fixed rain sounds appearing in Sacrament Interiors • Fixed enchantment-specific weapon whooshes cutting a bit too early • Fixed NPCs not making footstep sounds when walking around • Fixed environment states sometimes not resetting when returning to the main menu ⚔️ VFX: • Blood effects are now juicier and used more often! • Improved blood visual effects attachment to characters bodies from attacking and getting hit • Increased intensity of shiny item drop VFX ⚔️ Bounties and Challenges: • Updated Crustacean Conundrum bounty to spawn 14 Crabs while still only requiring 8 Crabs be killed to complete ⚔️ Localization: • Added and updated localized text in many places across multiple languages • Added localization support for new Controller Remapping screen and for various missing localized elements • Fixed incorrect font on the Activities screen ⚔️ Bug Fixes: • Fixed various enchantments on unique weapons and rings that weren’t working properly • Fixed Rested Bonuses for sleeping in beds • Fixed Key Items respawning after pick up • Fixed navigation in Nameless Pass which was preventing certain enemies and the Riven Twins boss from patrolling and moving to the player • Fixed Echo Knight falling off the arena and blocking progress • Fixed Cerim Armor missing upgrades at Filmore • Fixed Risen Pavise, Eye of the Beholder and Wooden Howler Shields not showing their proper models • Fixed SHIFT key not being recognized in the Main Menu • Fixed certain environment textures overriding certain armor textures • Fixed certain armor having missing or incorrect cloth simulation • Fixed rigging on certain armor • Fixed The Wallow boss attacks not having sound effects • Fixed Falling Sky Blueprint not giving the Unique version of the weapon when crafting • Fixed an issue where completed but not yet turned in bounty/challenge rewards were being automatically given to the player at reset • Fixed wall cannons not firing in Cerim Crucible • Fixed XP UI not showing “Max Level” after reaching the level cap • Fixed Level and XP UI being present without a Character selected in the Main Menu • Fixed “Long Area Name” appearing on the map where map is unavailable (such as Cerim Crucible) • Fixed being able to skip through locked doors in The Shallows • Fixed players getting stuck at the end of the entrance corridor in the Echo Knight Arena • Fixed Enchant Item Challenge counting enchanted items that are picked up • Fixed mortuary guard popping in on screen during Spoken and Unspoken quest • Fixed extra Elsa map marker during the Spoken and Unspoken quest • Fixed Giles and Petra standing instead of sitting on the chairs in Caroline’s Inn • Fixed Arrows not hitting Plagued Wolf • Fixed Wolf and Plagued Wolf target point • Fixed Tanth Knight getting stuck during patrolling in Mariner’s Keep at Endgame state • Fixed Darak leaving his shield in Orban Glades when he escapes • Fixed chest opening VFX in Performance and Balanced quality presets • Fixed Wolf having a dance party after death • Fixed Chest floating in the air in Mariner’s Keep • Fixed incorrect texture on the Crafting Table • Fixed 4096x2160 resolution appearing as 256x135 aspect ratio, instead displays as 1.9:1 • Fixed overblown bonfire lighting at The Shallows • Removed rogue rim light at The Shallows • Removed lighting debug shortcut See the full patch notes here -
1:30

🛠️ Patch Notes - Early Access Patch 2 We are incredibly excited to be releasing our largest patch yet, marking the One Month Anniversary of our Steam Early Access Launch! Patch 2 is chock full of highly requested features such as Weapon Tryout, the ability to Respec, DLSS / FSR Upscaling and Controller Remapping. Lots of Balancing and Quality of Life improvements, Audio, Animation, and Visual Effect polish as well as a multitude of bug fixes are also included! Between DLSS and FSR, numerous CPU, GPU performance improvements, and memory optimization we are confident that your experience of playing No Rest For The Wicked will be significantly smoother across a wide range of hardware. For NVIDIA users, we are excited to mention that there’s a new Game Ready Driver for No Rest for the Wicked! Be sure to check out our Patch 2 Highlight Video and the full patch notes below. ⚔️ Performance: • Performance Mode now lowers texture resolution, reducing crashes on lower-end machines • Numerous Significant CPU optimizations • Fixed performance degradation that might occur on some gamepads • Fixed numerous memory leaks • Reduced instantiation spikes for numerous objects • Disabled detail meshes on generic humanoids faces when not needed • Reduced latency, overhead and improved stability of GPU Culling • Optimized texture resolution and memory budgets for Steam Deck • Optimized Art content in Ship Prologue and its cinematics • Removed unused weapon assets to free up memory • Removed leftover developer tools to free up memory • Optimized CPU spikes of a variety of common content loading operations • Added texture streaming for character portraits during dialogue interactions to save memory • Fixed some persistent log spam being generated by potatoes in Nameless Pass • Cleaned up numerous NPC prefabs, reducing memory footprint and instantiation costs • Optimized Ambient Occlusion Rendering • Extended GPU culling usage for more cases • Configured and optimized pooling for more prefab instantiations reducing CPU spikes ⚔️ Gameplay Systems: • Added new Respec System! ⚬ Players can now Respec by examining the statue in the Cerim Crucible Atrium ⚬ Respec allows players to take back Attribute Points that have been allocated at the cost of 1 Fallen Ember per Attribute Point returned ⚬ Players can then allocate returned Attribute Points for no cost at the Respec screen or in the existing Stats screen ⚔️ Quality of Life: • All weapons can now be equipped regardless of their Attribute Requirements to allow players to try out weapons they acquire ⚬ Weapons that the player does not meet the requirements for will deal less damage through negative scaling on the Attributes that are below the weapon’s Attribute Requirements • Inventory Items can now be docked to compare them ⚬ Press F (Keyboard) or Y (Controller) to dock items and hover other items to compare • Brought back the Misc category to the Inventory ⚬ Housing items, Runes, Fallen Embers and other miscellaneous items will now be sorted into this category and free up space from other categories • Vendor screens are now sorted by item type so that items are more organized for purchase • Improved Stamina player HUD brightness for better visibility, and readability of stamina debt • Added side notifications for when Danos Sacrament Upgrades are completed • Added Floor Indicators under the Clock HUD to show the Cerim Crucible floors • Improved visibility of LB/RB button icons for Equipment HUD on Steam Deck ⚔️ Settings: • Added support for Upscaling with DLSS 3.7 and FSR 2.2 • Added custom key rebinding options for Controller • Added support for Mouse Buttons 4,5 and F1-F12 Keys for custom Keyboard bindings • Default Keyboard layout set to Mouse+WASD • Added support for worldspace Player HUD (Stamina wheel, NPC name tags, etc) brightness to UI Brightness setting ⚔️ Content Additions: • Added a new set of enchantments • All Throw runes can now be added to Spears ⚔️ Loot: • Added Pig Sticker Blueprint to Fillmore's Level 1 Shop • Added Assegai Blueprint to Whittacker's Level 1 Shop ⚔️ Balance: • Nerfed Throw runes ⚬ Reduced Poise Damage on all Throw runes ⚬ Reduced Damage on Ice Throw Rune • Nerfed Focus Regeneration enchant curve so that it no longer generates too much Focus too quickly • Focus Regeneration enchantment no longer drops with Gloves and now only drops with Helmets • This includes enchanting items at Eleanor • Falling Sky and Woodland Protector’s initial item levels were set too high and have been lowered to the intended levels ⚔️ Weapons: • Updated animation for backstabbing with Staves, Spears, Greatswords and Great Hammers • Updated visual effects for Piercing type weapon attacks (such as Spear or Rapier) ⚔️ Enemies and Bosses: • Polished Darak boss fight ⚬ Improved behavior to prevent him standing idle after attacking ⚬ Improved behavior when fighting ranged builds • Added Bite Attack to Plague Rat • Added Back Attack to Risen Axe Bruiser • Added escape logic to Risen Fire Bomber • Added Elemental Affix visual effects to Nith Brute, Nith Screamer and Shackled Brute • Adding cloth simulation to Boarskin Bruiser • Polished rigging on Plagued Boomer • Reduced camera shake intensity on Risen Hammer Bruiser, Boarskin Bruiser and Riven Twins • Smaller enemies can now smash breakable objects (barrels, crates, etc.) ⚔️ NPCs: • Changed the name of the worried woman in the Sacrament Town Square to Nell • Polishing dialog for Druo, Lucian and Everwyn • Updated the dialog for NPCs at the Cerim Gate in Nameless Pass • Added eavesdrop to Sleeping Guard Gerard in Sacrament ⚔️ Areas: • Improved collision, faders and set dressing in Prologue Ship, Orban Glades, Mariner’s Keep, Nameless Pass, Sacrament, Multiple Sacrament Interiors, Cerim Crucible, Cerim Cave, Riven Twins Boss Arena and Potion Seller Cave • Polished lighting for the ship in Prologue, Sacrament and Cerim Crucible • Updated foliage in various locations • Added physics and wind simulation to Spruce trees ⚔️ Cinematics: • Polished animations for characters in the Inquisition Arrival cinematic • Improved lighting, character rim lighting and volumetrics for the Prologue Ship Crash Outro and Inquisition Arrival cinematics • Removed a background character who was blocking part of the view in the Inquisition Arrival cinematic • Fixed cloth and camera pops in the Inquisition Arrival cinematic ⚔️ Audio: • Environment update for Sacrament: ⚬ Added Ambience Emitters for certain Residential and Vendor buildings like the Cook, Tavern, Woodcrafter and Enchantress ⚬ Updated zone beds and oneshots for unique parts of town (Cemetery, Poor Area,Training Grounds, Dasha Sanctuary) ⚬ The church near the cemetery now has bells ringing to service playing at certain times of day, followed by churchgoers praying and chanting from behind the doors. ⚬ Updated ambience for Sacrament Town Square to feel busier during the day ⚬ Updated environment audio for the Cerim Gate zone in Mountain Pass • Increased audio buffer to help alleviate audio crackle artifacts • Increased available audio resources to help prevent sounds from dropping out during long play sessions • Updated audio for Cerim Vision cinematic • Updated audio mix for Barrel and Crate destruction • Saluting Guards in Sacrament now have sound • Added Weapon-specific Impacts on parrying and blocking actions • Added ladder sliding sound effects for Kickdown Ladders • Added sound effects for going down Ladders • Added new sound effects for Plague-Enchanted weapons • Polished audio for Bounties enemies • Fixed missing sounds for Plagued Mutant Soldier • Fixed rain sounds appearing in Sacrament Interiors • Fixed enchantment-specific weapon whooshes cutting a bit too early • Fixed NPCs not making footstep sounds when walking around • Fixed environment states sometimes not resetting when returning to the main menu ⚔️ VFX: • Blood effects are now juicier and used more often! • Improved blood visual effects attachment to characters bodies from attacking and getting hit • Increased intensity of shiny item drop VFX ⚔️ Bounties and Challenges: • Updated Crustacean Conundrum bounty to spawn 14 Crabs while still only requiring 8 Crabs be killed to complete ⚔️ Localization: • Added and updated localized text in many places across multiple languages • Added localization support for new Controller Remapping screen and for various missing localized elements • Fixed incorrect font on the Activities screen ⚔️ Bug Fixes: • Fixed various enchantments on unique weapons and rings that weren’t working properly • Fixed Rested Bonuses for sleeping in beds • Fixed Key Items respawning after pick up • Fixed navigation in Nameless Pass which was preventing certain enemies and the Riven Twins boss from patrolling and moving to the player • Fixed Echo Knight falling off the arena and blocking progress • Fixed Cerim Armor missing upgrades at Filmore • Fixed Risen Pavise, Eye of the Beholder and Wooden Howler Shields not showing their proper models • Fixed SHIFT key not being recognized in the Main Menu • Fixed certain environment textures overriding certain armor textures • Fixed certain armor having missing or incorrect cloth simulation • Fixed rigging on certain armor • Fixed The Wallow boss attacks not having sound effects • Fixed Falling Sky Blueprint not giving the Unique version of the weapon when crafting • Fixed an issue where completed but not yet turned in bounty/challenge rewards were being automatically given to the player at reset • Fixed wall cannons not firing in Cerim Crucible • Fixed XP UI not showing “Max Level” after reaching the level cap • Fixed Level and XP UI being present without a Character selected in the Main Menu • Fixed “Long Area Name” appearing on the map where map is unavailable (such as Cerim Crucible) • Fixed being able to skip through locked doors in The Shallows • Fixed players getting stuck at the end of the entrance corridor in the Echo Knight Arena • Fixed Enchant Item Challenge counting enchanted items that are picked up • Fixed mortuary guard popping in on screen during Spoken and Unspoken quest • Fixed extra Elsa map marker during the Spoken and Unspoken quest • Fixed Giles and Petra standing instead of sitting on the chairs in Caroline’s Inn • Fixed Arrows not hitting Plagued Wolf • Fixed Wolf and Plagued Wolf target point • Fixed Tanth Knight getting stuck during patrolling in Mariner’s Keep at Endgame state • Fixed Darak leaving his shield in Orban Glades when he escapes • Fixed chest opening VFX in Performance and Balanced quality presets • Fixed Wolf having a dance party after death • Fixed Chest floating in the air in Mariner’s Keep • Fixed incorrect texture on the Crafting Table • Fixed 4096x2160 resolution appearing as 256x135 aspect ratio, instead displays as 1.9:1 • Fixed overblown bonfire lighting at The Shallows • Removed rogue rim light at The Shallows • Removed lighting debug shortcut See the full patch notes here -

No Rest for the Wicked

184,300 次观看 • 2 年前

what is "retail" and what can be today? it's wild how little attention this space gets tbh retail isn't just about profit margins & sales conversions - it's this fascinating bridge between innovation culture & everyday life, especially in design and fashion but nobody's really cracked it for virtual spaces yet all the worlds by dolce gabbana and others are like a very low effort interfaces that dont talk enough to the real user, it is a marketing move to say we did that, we follow tech bla bla (imo :) spent months researching traditional retail spaces - marble floors + high ceilings + that specific type of lighting that makes everything look expensive + trained staff in perfectly pressed + ironed uniforms - it's all carefully orchestrated then you've got these sleek 2d websites - full screen product shots + bold typography + minimal clicks to checkout - they work but something's missing, that human element that makes physical retail special started building this hybrid concept back in october 23 - imagine a web-based spatial store where your digital twin can actually try stuff on instantly - no more guessing if that jacket fits your avatar retail spaces are like these sacred temples of brand culture - acne stores hit different than zara ones & that's intentional - each space tells a story about what the brand believes in metaverse retail flips this whole concept - instead of walking 20 mins to a store you're literally one click away from being inside this carefully crafted virtual environment - ai npcs that actually understand fashion & can help you find exactly what you're looking for here's the thing about virtual retail - it's not just about pushing products - created this space where you can just vibe, test out avatars, play with different looks - if you buy something cool but the experience matters more. feeling same for the stores, new gen irl stores switched the narrative to a spaces where you can have an espresso and chill these ai npcs are different - they're not following you around like those overeager sales assistants - they're just chilling in the space, ready to help if you need them but totally cool if you just want to explore went through like 12 different iterations of interior design thru 3 years - each version taught something new about how people interact with virtual fashion - it's wild how much user behavior in virtual spaces differs from physical retail realized something big during development - creating the collection isn't even half the battle anymore - the way you present it, the whole experience around it, that's become this massive design challenge it's like gesamtkunstwerk but for the metaverse - every single element needs to be intentional - the lighting, the sound design, the way avatars move through the space - it all matters built this whole ecosystem around the concept - the store connects to the runway experience connects to the website connects to the marketplace - everything flows together serving this bigger vision of what virtual fashion can be this isn't just about selling digital clothes - it's about creating this accessible gateway into 3d internet culture - making virtual fashion something that actually makes sense in people's daily digital lives the lighting system alone took a month - because shadows & reflections hit different in virtual space - needed to make materials look good but also render fast enough for smooth experience on todays low gpu vr machine devices future of retail isn't physical or digital - it's this wild hybrid space where real & virtual blend together - imagine walking into a physical store & seeing your virtual wardrobe projected onto your reflection looking at the data now - users spend avg 23 mins in the virtual store compared to 7 mins on traditional e-commerce sites - they're not just shopping, they're exploring & connecting with the brand story accessibility was key in design - wanted anyone with a decent internet connection to access this space - no fancy vr gear required just your browser & imagination each virtual store could visit generates this unique experience - in future, the space can remember your preferences but also introduces new elements each time - keeps the discovery feeling fresh what's wild is how this changes the whole fashion calendar - virtual retail spaces can transform instantly - new collection drops can completely reshape the environment in seconds - no more seasonal renovations, change the glb. looking ahead this could revolutionize how we think about brand spaces - why limit yourself to physics when your store could literally defy gravity - imagine trying on a jacket while floating through a nebula retail in metaverse isn't just about replicating physical stores - it's about creating these impossible spaces that still somehow feel familiar & welcoming - that's the sweet spot we're all chasing built this thinking about the next wave of digital natives - they're gonna expect these kinds of hybrid experiences - traditional e-commerce gonna feel as outdated as catalog shopping feels to us now the tech's finally catching up to the vision - webgl performance + ai integration + virtual try-on tech all hitting that sweet spot where imagination meets practicality all my thoughts here are quite alpha in sense of applying today, was able to apply only some of them thanks to hyperfy, but the vision is here. breathe it. now with v2, all of these thoughts can be applied and developped. this is just the beginning tbh - every problem solved opens up new possibilities - excited to see how others build on these concepts & push virtual retail even further. fubu side note: made an ai gen notorious big song for it, enjoyy.
6:31

what is "retail" and what can be today? it's wild how little attention this space gets tbh retail isn't just about profit margins & sales conversions - it's this fascinating bridge between innovation culture & everyday life, especially in design and fashion but nobody's really cracked it for virtual spaces yet all the worlds by dolce gabbana and others are like a very low effort interfaces that dont talk enough to the real user, it is a marketing move to say we did that, we follow tech bla bla (imo :) spent months researching traditional retail spaces - marble floors + high ceilings + that specific type of lighting that makes everything look expensive + trained staff in perfectly pressed + ironed uniforms - it's all carefully orchestrated then you've got these sleek 2d websites - full screen product shots + bold typography + minimal clicks to checkout - they work but something's missing, that human element that makes physical retail special started building this hybrid concept back in october 23 - imagine a web-based spatial store where your digital twin can actually try stuff on instantly - no more guessing if that jacket fits your avatar retail spaces are like these sacred temples of brand culture - acne stores hit different than zara ones & that's intentional - each space tells a story about what the brand believes in metaverse retail flips this whole concept - instead of walking 20 mins to a store you're literally one click away from being inside this carefully crafted virtual environment - ai npcs that actually understand fashion & can help you find exactly what you're looking for here's the thing about virtual retail - it's not just about pushing products - created this space where you can just vibe, test out avatars, play with different looks - if you buy something cool but the experience matters more. feeling same for the stores, new gen irl stores switched the narrative to a spaces where you can have an espresso and chill these ai npcs are different - they're not following you around like those overeager sales assistants - they're just chilling in the space, ready to help if you need them but totally cool if you just want to explore went through like 12 different iterations of interior design thru 3 years - each version taught something new about how people interact with virtual fashion - it's wild how much user behavior in virtual spaces differs from physical retail realized something big during development - creating the collection isn't even half the battle anymore - the way you present it, the whole experience around it, that's become this massive design challenge it's like gesamtkunstwerk but for the metaverse - every single element needs to be intentional - the lighting, the sound design, the way avatars move through the space - it all matters built this whole ecosystem around the concept - the store connects to the runway experience connects to the website connects to the marketplace - everything flows together serving this bigger vision of what virtual fashion can be this isn't just about selling digital clothes - it's about creating this accessible gateway into 3d internet culture - making virtual fashion something that actually makes sense in people's daily digital lives the lighting system alone took a month - because shadows & reflections hit different in virtual space - needed to make materials look good but also render fast enough for smooth experience on todays low gpu vr machine devices future of retail isn't physical or digital - it's this wild hybrid space where real & virtual blend together - imagine walking into a physical store & seeing your virtual wardrobe projected onto your reflection looking at the data now - users spend avg 23 mins in the virtual store compared to 7 mins on traditional e-commerce sites - they're not just shopping, they're exploring & connecting with the brand story accessibility was key in design - wanted anyone with a decent internet connection to access this space - no fancy vr gear required just your browser & imagination each virtual store could visit generates this unique experience - in future, the space can remember your preferences but also introduces new elements each time - keeps the discovery feeling fresh what's wild is how this changes the whole fashion calendar - virtual retail spaces can transform instantly - new collection drops can completely reshape the environment in seconds - no more seasonal renovations, change the glb. looking ahead this could revolutionize how we think about brand spaces - why limit yourself to physics when your store could literally defy gravity - imagine trying on a jacket while floating through a nebula retail in metaverse isn't just about replicating physical stores - it's about creating these impossible spaces that still somehow feel familiar & welcoming - that's the sweet spot we're all chasing built this thinking about the next wave of digital natives - they're gonna expect these kinds of hybrid experiences - traditional e-commerce gonna feel as outdated as catalog shopping feels to us now the tech's finally catching up to the vision - webgl performance + ai integration + virtual try-on tech all hitting that sweet spot where imagination meets practicality all my thoughts here are quite alpha in sense of applying today, was able to apply only some of them thanks to hyperfy, but the vision is here. breathe it. now with v2, all of these thoughts can be applied and developped. this is just the beginning tbh - every problem solved opens up new possibilities - excited to see how others build on these concepts & push virtual retail even further. fubu side note: made an ai gen notorious big song for it, enjoyy.

decentralize*

12,505 次观看 • 1 年前

Making Sense Of Bitcoin Treasury Companies If you've been following me on X you’ll know that I have recently been floating a lot of my updated thoughts on the Bitcoin Treasury space. Here I have synthesised all of my ideas and distilled them into a single video. If you prefer YouTube, you can find the link in the comments. If you prefer written format, continue reading. The first thing we need to do is acknowledge an important fact which is that Strategy, as a Bitcoin Treasury Company, is an anomaly. What do I mean by that? Strategy’s success has been defined by a number of unique factors and circumstances, most of which cannot be replicated again by other Bitcoin Treasury Companies. Specifically, there are 6 things that stand out to me. 1. Before adopting Bitcoin, Strategy was a billion dollar company with an operating business that was generating roughly $50M in cash a year. 2. Until the introduction of the ETF's in January 2024, Strategy was the only way for the average investor to gain passive exposure to Bitcoin. 3. Until this year, Strategy was the only way for the average investor to gain leveraged exposure to Bitcoin. 4. Strategy was issuing multiple, billion dollar, zero coupon, unsecured convertible notes at +50% conversion premiums. 5. Strategy has Michael Saylor, who, you don’t need me to tell you, is in a league of his own. 6. For many reasons, including those I’ve just mentioned, Strategy has benefitted disproportionately from the broader sentiment around Bitcoin. In other words, for the best part of 4 years, Strategy had zero competition for either capital or attention. As a result, it became a magnet for capital from anyone who wanted exposure to Bitcoin and it attracted inflows that were beyond what fundamentals alone would maybe justify. Therefore, using Strategy as a blueprint for the performance that you can expect from other Bitcoin Treasury Companies is a bad idea. Using Strategy as a blueprint for how to operate a Bitcoin Treasury Company is a good idea. Now let’s break down what’s unfolded over the last 6 months or so. Between May and June of this year, when we witnessed a flood of new Bitcoin Treasury Companies, we entered what I refer to as the frenzy phase. The frenzy phase was driven almost entirely by sentiment. By sentiment I simply mean emotion. Since then, as sentiment has slowly faded, the market has increasingly priced Bitcoin Treasury Companies based more on fundamentals. By fundamentals I simply mean facts. So where as sentiment is driven by emotion and hype, fundamentals are driven by facts and reason. The problem is that when you price Bitcoin Treasury Companies on fundamentals, you realise that many of them are almost entirely dependent on sentiment in order to expand mNAV so they can raise capital via the common stock ATM to buy Bitcoin and generate Bitcoin Yield. However, for me, raising capital via the common stock ATM and recycling it into Bitcoin is not genuine value creation — it’s value transfer. That’s not to say you shouldn’t leverage the ATM as and when necessary — you should. However, if your business model as a Bitcoin Treasury Company no longer works when “sentiment is low” then you have neither a business model nor a business. You’re the equivalent of a meme stock except with Bitcoin on your balance sheet. On that basis, companies shouldn’t expect to trade at a premium if the common stock ATM is the only way they raise capital. I’m not saying they won’t trade at a premium — I’m saying that companies shouldn’t expect to. Now, between July and now, we’ve obviously seen mNAVs compress substantially and so the frenzy phase is over which means that the days of automatically being granted generous mNAV multiples is also over. So now we are in the maturity phase. The maturity phase is going to be defined by being able to offer a differentiated value proposition and having a sustainable business model that can generate Bitcoin Yield in any environment independent of sentiment. In other words, they can generate Bitcoin Yield when trading at or below 1 mNAV. So essentially now, Bitcoin Treasury Companies have to work for their mNAV multiples — as it should be. Following the maturity phase will be the consolidation phase where capital, Bitcoin and ultimately market share will converge towards a small number of Bitcoin Treasury Companies that will dominate the entire industry. I should clarify that I am referring predominantly to pure-play Bitcoin Treasury Companies — companies who are valued based solely on their Bitcoin strategy. Now, with everything that I’ve said, how should you evaluate Bitcoin Treasury Companies? Hopefully over the next few weeks I’m going to string together a video with my valuation framework. In the meantime, a basic test is that I use is this: How much Bitcoin Yield can the company generate over X period of time — you decide what that period of time is — if it traded at 1x mNAV over that entire period? If the answer is 0, then they are probably entirely dependent on raising capital via the common stock ATM which means they likely don’t deserve a premium. If the answer is >0, then they are probably innovating through the use of other instruments — like converts and preferred products — which means they likely do deserve a premium and so whatever number you come up with should be used as the base for your valuation. Now, don’t be fooled. The Bitcoin Treasury Company space is, not entirely, but to a large degree, a zero-sum game. Every Dollar raised by one Bitcoin Treasury Company is at the expense of every other Bitcoin Treasury Company. Every Bitcoin purchased by one Bitcoin Treasury Company is at the expense of every other Bitcoin Treasury Company. It’s only because we are early that everyone is incentivised to essentially hold hands and cheer each other on. However, make no mistake, everyone involved is tacitly well aware that they are all competing for the same finite amount of capital and the same fixed amount of Bitcoin. Thus, the reality is that, by definition, not every Bitcoin Treasury Company is going to succeed. So choose your horses and jockeys wisely. As a side note, with the amount of Bitcoin Treasury Companies now desperately chasing and competing for the same capital from institutions, who do you think has the leverage; the Bitcoin Treasury Companies or the institutions? I’ll let you decide. Before I close, I want to leave you guys with this. There is a small subset of people invested in Bitcoin Treasury Companies who are desperately clinging on to their bags because they believe “sentiment will return.” These people are completely missing the point. My friends, if your investing philosophy is based on sentiment, you are simply not going to last. You want to base your decisions, as far as possible, on fundamentals. As investors, you either adapt and update your mental models based on how things are and not how you want them to be — or you get left behind. With that in mind: Never get caught up in tribalism. Never get attached to your beliefs. Always think critically. Always think independently. Always seek Truth.
10:20

Making Sense Of Bitcoin Treasury Companies If you've been following me on X you’ll know that I have recently been floating a lot of my updated thoughts on the Bitcoin Treasury space. Here I have synthesised all of my ideas and distilled them into a single video. If you prefer YouTube, you can find the link in the comments. If you prefer written format, continue reading. The first thing we need to do is acknowledge an important fact which is that Strategy, as a Bitcoin Treasury Company, is an anomaly. What do I mean by that? Strategy’s success has been defined by a number of unique factors and circumstances, most of which cannot be replicated again by other Bitcoin Treasury Companies. Specifically, there are 6 things that stand out to me. 1. Before adopting Bitcoin, Strategy was a billion dollar company with an operating business that was generating roughly $50M in cash a year. 2. Until the introduction of the ETF's in January 2024, Strategy was the only way for the average investor to gain passive exposure to Bitcoin. 3. Until this year, Strategy was the only way for the average investor to gain leveraged exposure to Bitcoin. 4. Strategy was issuing multiple, billion dollar, zero coupon, unsecured convertible notes at +50% conversion premiums. 5. Strategy has Michael Saylor, who, you don’t need me to tell you, is in a league of his own. 6. For many reasons, including those I’ve just mentioned, Strategy has benefitted disproportionately from the broader sentiment around Bitcoin. In other words, for the best part of 4 years, Strategy had zero competition for either capital or attention. As a result, it became a magnet for capital from anyone who wanted exposure to Bitcoin and it attracted inflows that were beyond what fundamentals alone would maybe justify. Therefore, using Strategy as a blueprint for the performance that you can expect from other Bitcoin Treasury Companies is a bad idea. Using Strategy as a blueprint for how to operate a Bitcoin Treasury Company is a good idea. Now let’s break down what’s unfolded over the last 6 months or so. Between May and June of this year, when we witnessed a flood of new Bitcoin Treasury Companies, we entered what I refer to as the frenzy phase. The frenzy phase was driven almost entirely by sentiment. By sentiment I simply mean emotion. Since then, as sentiment has slowly faded, the market has increasingly priced Bitcoin Treasury Companies based more on fundamentals. By fundamentals I simply mean facts. So where as sentiment is driven by emotion and hype, fundamentals are driven by facts and reason. The problem is that when you price Bitcoin Treasury Companies on fundamentals, you realise that many of them are almost entirely dependent on sentiment in order to expand mNAV so they can raise capital via the common stock ATM to buy Bitcoin and generate Bitcoin Yield. However, for me, raising capital via the common stock ATM and recycling it into Bitcoin is not genuine value creation — it’s value transfer. That’s not to say you shouldn’t leverage the ATM as and when necessary — you should. However, if your business model as a Bitcoin Treasury Company no longer works when “sentiment is low” then you have neither a business model nor a business. You’re the equivalent of a meme stock except with Bitcoin on your balance sheet. On that basis, companies shouldn’t expect to trade at a premium if the common stock ATM is the only way they raise capital. I’m not saying they won’t trade at a premium — I’m saying that companies shouldn’t expect to. Now, between July and now, we’ve obviously seen mNAVs compress substantially and so the frenzy phase is over which means that the days of automatically being granted generous mNAV multiples is also over. So now we are in the maturity phase. The maturity phase is going to be defined by being able to offer a differentiated value proposition and having a sustainable business model that can generate Bitcoin Yield in any environment independent of sentiment. In other words, they can generate Bitcoin Yield when trading at or below 1 mNAV. So essentially now, Bitcoin Treasury Companies have to work for their mNAV multiples — as it should be. Following the maturity phase will be the consolidation phase where capital, Bitcoin and ultimately market share will converge towards a small number of Bitcoin Treasury Companies that will dominate the entire industry. I should clarify that I am referring predominantly to pure-play Bitcoin Treasury Companies — companies who are valued based solely on their Bitcoin strategy. Now, with everything that I’ve said, how should you evaluate Bitcoin Treasury Companies? Hopefully over the next few weeks I’m going to string together a video with my valuation framework. In the meantime, a basic test is that I use is this: How much Bitcoin Yield can the company generate over X period of time — you decide what that period of time is — if it traded at 1x mNAV over that entire period? If the answer is 0, then they are probably entirely dependent on raising capital via the common stock ATM which means they likely don’t deserve a premium. If the answer is >0, then they are probably innovating through the use of other instruments — like converts and preferred products — which means they likely do deserve a premium and so whatever number you come up with should be used as the base for your valuation. Now, don’t be fooled. The Bitcoin Treasury Company space is, not entirely, but to a large degree, a zero-sum game. Every Dollar raised by one Bitcoin Treasury Company is at the expense of every other Bitcoin Treasury Company. Every Bitcoin purchased by one Bitcoin Treasury Company is at the expense of every other Bitcoin Treasury Company. It’s only because we are early that everyone is incentivised to essentially hold hands and cheer each other on. However, make no mistake, everyone involved is tacitly well aware that they are all competing for the same finite amount of capital and the same fixed amount of Bitcoin. Thus, the reality is that, by definition, not every Bitcoin Treasury Company is going to succeed. So choose your horses and jockeys wisely. As a side note, with the amount of Bitcoin Treasury Companies now desperately chasing and competing for the same capital from institutions, who do you think has the leverage; the Bitcoin Treasury Companies or the institutions? I’ll let you decide. Before I close, I want to leave you guys with this. There is a small subset of people invested in Bitcoin Treasury Companies who are desperately clinging on to their bags because they believe “sentiment will return.” These people are completely missing the point. My friends, if your investing philosophy is based on sentiment, you are simply not going to last. You want to base your decisions, as far as possible, on fundamentals. As investors, you either adapt and update your mental models based on how things are and not how you want them to be — or you get left behind. With that in mind: Never get caught up in tribalism. Never get attached to your beliefs. Always think critically. Always think independently. Always seek Truth.

Chris Millas

34,483 次观看 • 9 个月前

Experience with the new Sentient Chat update: Smooth travel planning + super concise 24h Crypto news! 🧑‍💻I just tested the update and… honestly impressed. With just a few prompts, I received two completely different yet equally exciting experiences. In the video, I asked a series of questions to test its research capabilities and how well it could deliver the best results. Below is what I got back 👇 1/ Plan Your Travel – Detailed itineraries, ready for “Instagram-worthy” shots 🧳✈️ I tried asking: “If I want to explore Instagram-worthy cafés in Seoul, what’s the best 2-day route?” Sentient Chat returned a clear 2-day itinerary in table format: - Daily neighborhoods, must-go cafés, suggested time slots, subway + walking directions, and even “Why this route works” (reasoning behind the choices, optimized for time and transfers). Then I added another prompt: “What should I pack for Da Lat in December?” I immediately got a packing checklist broken down by clothing layers, accessories, electronics, and local culture tips. It felt like having a personal travel planner: -> No unnecessary clutter, no need to search through 10 more tabs. 🤔What I liked: - Structured presentation (tables, checklists) makes it easy to save and follow. - Practical “photo-op” and “how to get there” suggestions. Not just telling me where to go but also why to go there -> exactly the kind of plan you can use right away. This really impressed me because Sentient Chat understands our mindset: - Wanting the most comfortable travel experience while also suggesting plans for perfect photo spots. 2/ News Bites – Super thorough 24h Crypto market summary 📉 I asked: “Give me a quick update on the crypto market over the last 24 hours.” The result included: Market snapshot: total market cap, 24h volume, dominance breakdown. - BTC/ETH price movements and market share. Sentiment from the Fear & Greed Index. Quick take-aways: for example “bearish pressure,” and current support/psychological levels being tested. -> It also came with concise notes that helped me grasp the overall picture in just 1–2 minutes. What I liked: Data aggregated from multiple sources (data providers) and condensed into a handful of the most important points. Concise language, with actionable insights (support/resistance, risk notes) instead of just numbers. Perfect to drop into my daily recap or use as a morning brief for the community. 🤔Why I think this update is excellent One-stop: Both precise travel planning and 24h crypto news bites – all in one place. High applicability: - Outputs in table/checklist/take-away format -> just copy-paste into posts or decks. Community-oriented: - Results are transparent, based on multiple open sources -> reducing bias, increasing accuracy. - Suggested prompts you can try like I did (you can change the city) - Travel: “Plan a 2-day IG-friendly café route in Seoul with subway directions and timeslots.” - Travel: “Packing checklist for Da Lat in December with local customs tips.” - Crypto: “Summarize the last 24h crypto market: market cap, volume, BTC/ETH, dominance, sentiment, and 3 key takeaways.” 🧑‍💻Conclusion: The new Sentient Chat update perfectly captures the spirit of “AI for the community, used in real life” On one side, it helps you travel smart, save time, and capture great shots. On the other, it delivers a clear, well-founded view of the 24h market. If you’re someone who values time optimization and quick decision-making based on data, this beta update is absolutely worth trying. Shad Haq Cassian RANA #SentientAGI
1:37

Experience with the new Sentient Chat update: Smooth travel planning + super concise 24h Crypto news! 🧑‍💻I just tested the update and… honestly impressed. With just a few prompts, I received two completely different yet equally exciting experiences. In the video, I asked a series of questions to test its research capabilities and how well it could deliver the best results. Below is what I got back 👇 1/ Plan Your Travel – Detailed itineraries, ready for “Instagram-worthy” shots 🧳✈️ I tried asking: “If I want to explore Instagram-worthy cafés in Seoul, what’s the best 2-day route?” Sentient Chat returned a clear 2-day itinerary in table format: - Daily neighborhoods, must-go cafés, suggested time slots, subway + walking directions, and even “Why this route works” (reasoning behind the choices, optimized for time and transfers). Then I added another prompt: “What should I pack for Da Lat in December?” I immediately got a packing checklist broken down by clothing layers, accessories, electronics, and local culture tips. It felt like having a personal travel planner: -> No unnecessary clutter, no need to search through 10 more tabs. 🤔What I liked: - Structured presentation (tables, checklists) makes it easy to save and follow. - Practical “photo-op” and “how to get there” suggestions. Not just telling me where to go but also why to go there -> exactly the kind of plan you can use right away. This really impressed me because Sentient Chat understands our mindset: - Wanting the most comfortable travel experience while also suggesting plans for perfect photo spots. 2/ News Bites – Super thorough 24h Crypto market summary 📉 I asked: “Give me a quick update on the crypto market over the last 24 hours.” The result included: Market snapshot: total market cap, 24h volume, dominance breakdown. - BTC/ETH price movements and market share. Sentiment from the Fear & Greed Index. Quick take-aways: for example “bearish pressure,” and current support/psychological levels being tested. -> It also came with concise notes that helped me grasp the overall picture in just 1–2 minutes. What I liked: Data aggregated from multiple sources (data providers) and condensed into a handful of the most important points. Concise language, with actionable insights (support/resistance, risk notes) instead of just numbers. Perfect to drop into my daily recap or use as a morning brief for the community. 🤔Why I think this update is excellent One-stop: Both precise travel planning and 24h crypto news bites – all in one place. High applicability: - Outputs in table/checklist/take-away format -> just copy-paste into posts or decks. Community-oriented: - Results are transparent, based on multiple open sources -> reducing bias, increasing accuracy. - Suggested prompts you can try like I did (you can change the city) - Travel: “Plan a 2-day IG-friendly café route in Seoul with subway directions and timeslots.” - Travel: “Packing checklist for Da Lat in December with local customs tips.” - Crypto: “Summarize the last 24h crypto market: market cap, volume, BTC/ETH, dominance, sentiment, and 3 key takeaways.” 🧑‍💻Conclusion: The new Sentient Chat update perfectly captures the spirit of “AI for the community, used in real life” On one side, it helps you travel smart, save time, and capture great shots. On the other, it delivers a clear, well-founded view of the 24h market. If you’re someone who values time optimization and quick decision-making based on data, this beta update is absolutely worth trying. Shad Haq Cassian RANA #SentientAGI

David | Nimo

11,635 次观看 • 10 个月前

––Mathias Döpfner: Sam, is it actually true that your kind of favorite book is The Beginning of Infinity of Dieter Deutsch? Sam Altman: Yeah, I think if I had to pick one favorite book, I would pick that. ––Mathias Döpfner: Why is that so fascinating? Can you explain that? Sam Altman: Even if you don't read the whole thing, the first like 40-50 pages are, I think, the most wonderfully optimistic take on why, even in a world with AI, we're never going to run out of things to do and ways to be useful and problems to solve and things to explore. But I also think it explains so beautifully how we got here and why the relatively simple process that we've followed throughout human history got us to this incredible place. ––Mathias Döpfner: Okay, that's good, because David Deutsch, I think, is going to be our last virtual guest, at least tonight. David Deutsch is a physicist and scientist from Oxford University. And I think also you have disagreements with him about the possibility that artificial intelligence is transforming into superintelligence with consciousness, perhaps even. He thinks it cannot be the case. You think it should be the case. Here he is, David Deutsch. Welcome. And perhaps you can elaborate a little bit on that disagreement, but also why you admire Sam Altman. Sam Altman: Well, I don't care about that. I just want to hear your disagreement. David Deutsch: Okay, I can tell you. Well, on my computer, I keep a list of progress that has been achieved where I had previously been sure that it wasn't yet possible. One of the items I'm embarrassed to admit was the World Wide Web. Another was that I thought that no computer program would be able to sustain open-ended conversation on general subjects in natural language unless that program was an AGI, an artificial general intelligence. So it would have, I prefer to call, explanatory creativity. ChatGPT proved me wrong. It's not an AGI, and it can converse. That ability was a side effect of another, namely knowledge. The Eliza chatbot in the 1960s used little more than the words and phrases you told it. ChatGPT can chat about anything drawing on a vast body of knowledge, which was a phenomenally useful combination. For some people, too useful. They think they're speaking to a person, an AGI, just as the first users of Eliza treated it as if it were a person. Which brings me to a widespread myth of the Turing test. In reality, Alan Turing never proposed a test or benchmark for AGI. His imitation game wasn't a test of ethics, but a thought experiment to torpedo the intuition that machines can't think. Indeed, there can be no benchmark, because to be general, an AGI must be capable of choosing to remain silent. This is already a proof that AGI cannot be made via existing approaches, while those can and must be judged by benchmarks. Conversely, if something outputs a new explanation, you can't test for whether it created that or a human did, even you yourself when you administered the test. In Edison's phrase, there's the inspiration part, which only humans and AGIs can do, and the perspiration part, from which AGIs can liberate us. So, if there's no test, how do we know that humans are general intelligences? By telling their story. Human thought doesn't consist of mechanically converting motivations into actions, prompts into output. It's mainly about choosing motivations. Just as science is not extracting theories from data, it's seeing a problem, guessing explanations, criticizing and testing them. So how can you tell whether something is doing that? You can't, always. Sometimes it really is a bot you're chatting to, but when you have no explanation saying that you yourself are a bot, or that humans in general are, it's rational to assume that they aren't. Some people have fun questioning whether Einstein really created the theory of relativity or only assembled it mechanically from a smorgasbord of existing ideas. We know he created it because we know his story, what problems he was addressing, and why. Just as we know that Sam Altman, without having to write any code, brought ChatGPT into existence as a product and a phenomenon by having the intuition and the gumption to know that this was the right thing for humanity to try next. Nothing can program a computer to have such intuitions, yet. Sam Altman: Can I ask one question? David Deutsch: My guess. Sam Altman: You mentioned Einstein and general relativity, and I agree, I think that's one of the most beautiful things humanity's ever figured out. Maybe I would even say number one. And Einstein had a story, we knew what he was working on. If in a few years, GPT-8 figured out quantum gravity and could tell you its story of how it did it and the problems it was thinking about and why it decided to work on it, would But it still just looked like a language model output, but it was the real, it really did solve it. Would you call it like, then would you say, I appreciate that you keep a list of things you're wrong about. I do too. But would that be enough to convince you? David Deutsch: I think it would. Yeah. Sam Altman: All right. I'll take you up... David Deutsch: It's crucial here. Sam Altman: I agree to that as the test. ––Mathias Döpfner: David, thank you so much for joining us and thank you for your uplifting words and have a great evening. David Deutsch, a pioneer of quantum computing, one of the most brilliant thinkers of our times. Thank you for joining.
7:25

––Mathias Döpfner: Sam, is it actually true that your kind of favorite book is The Beginning of Infinity of Dieter Deutsch? Sam Altman: Yeah, I think if I had to pick one favorite book, I would pick that. ––Mathias Döpfner: Why is that so fascinating? Can you explain that? Sam Altman: Even if you don't read the whole thing, the first like 40-50 pages are, I think, the most wonderfully optimistic take on why, even in a world with AI, we're never going to run out of things to do and ways to be useful and problems to solve and things to explore. But I also think it explains so beautifully how we got here and why the relatively simple process that we've followed throughout human history got us to this incredible place. ––Mathias Döpfner: Okay, that's good, because David Deutsch, I think, is going to be our last virtual guest, at least tonight. David Deutsch is a physicist and scientist from Oxford University. And I think also you have disagreements with him about the possibility that artificial intelligence is transforming into superintelligence with consciousness, perhaps even. He thinks it cannot be the case. You think it should be the case. Here he is, David Deutsch. Welcome. And perhaps you can elaborate a little bit on that disagreement, but also why you admire Sam Altman. Sam Altman: Well, I don't care about that. I just want to hear your disagreement. David Deutsch: Okay, I can tell you. Well, on my computer, I keep a list of progress that has been achieved where I had previously been sure that it wasn't yet possible. One of the items I'm embarrassed to admit was the World Wide Web. Another was that I thought that no computer program would be able to sustain open-ended conversation on general subjects in natural language unless that program was an AGI, an artificial general intelligence. So it would have, I prefer to call, explanatory creativity. ChatGPT proved me wrong. It's not an AGI, and it can converse. That ability was a side effect of another, namely knowledge. The Eliza chatbot in the 1960s used little more than the words and phrases you told it. ChatGPT can chat about anything drawing on a vast body of knowledge, which was a phenomenally useful combination. For some people, too useful. They think they're speaking to a person, an AGI, just as the first users of Eliza treated it as if it were a person. Which brings me to a widespread myth of the Turing test. In reality, Alan Turing never proposed a test or benchmark for AGI. His imitation game wasn't a test of ethics, but a thought experiment to torpedo the intuition that machines can't think. Indeed, there can be no benchmark, because to be general, an AGI must be capable of choosing to remain silent. This is already a proof that AGI cannot be made via existing approaches, while those can and must be judged by benchmarks. Conversely, if something outputs a new explanation, you can't test for whether it created that or a human did, even you yourself when you administered the test. In Edison's phrase, there's the inspiration part, which only humans and AGIs can do, and the perspiration part, from which AGIs can liberate us. So, if there's no test, how do we know that humans are general intelligences? By telling their story. Human thought doesn't consist of mechanically converting motivations into actions, prompts into output. It's mainly about choosing motivations. Just as science is not extracting theories from data, it's seeing a problem, guessing explanations, criticizing and testing them. So how can you tell whether something is doing that? You can't, always. Sometimes it really is a bot you're chatting to, but when you have no explanation saying that you yourself are a bot, or that humans in general are, it's rational to assume that they aren't. Some people have fun questioning whether Einstein really created the theory of relativity or only assembled it mechanically from a smorgasbord of existing ideas. We know he created it because we know his story, what problems he was addressing, and why. Just as we know that Sam Altman, without having to write any code, brought ChatGPT into existence as a product and a phenomenon by having the intuition and the gumption to know that this was the right thing for humanity to try next. Nothing can program a computer to have such intuitions, yet. Sam Altman: Can I ask one question? David Deutsch: My guess. Sam Altman: You mentioned Einstein and general relativity, and I agree, I think that's one of the most beautiful things humanity's ever figured out. Maybe I would even say number one. And Einstein had a story, we knew what he was working on. If in a few years, GPT-8 figured out quantum gravity and could tell you its story of how it did it and the problems it was thinking about and why it decided to work on it, would But it still just looked like a language model output, but it was the real, it really did solve it. Would you call it like, then would you say, I appreciate that you keep a list of things you're wrong about. I do too. But would that be enough to convince you? David Deutsch: I think it would. Yeah. Sam Altman: All right. I'll take you up... David Deutsch: It's crucial here. Sam Altman: I agree to that as the test. ––Mathias Döpfner: David, thank you so much for joining us and thank you for your uplifting words and have a great evening. David Deutsch, a pioneer of quantum computing, one of the most brilliant thinkers of our times. Thank you for joining.

Deutsch Explains

63,456 次观看 • 10 个月前

HOW THE HOLOGRAPHIC SIMULATION WORKS (Update 12/11/24) Your ‘reality’ is a holographic projection that comes from your own eyes that are not like camera lenses, but literally projection lenses. How it works is complex, but here is the actual science. There is no such thing as material matter. It takes energy to cast something into fully visible 'solid' form (still a hologram). So as shown in Kirlian photography (spectrography) that shows the aura of things, you can see that even if you cut part of a leaf away, there is still an energy you normally won't see with your eyes that casts out the 'solid' form of that thing within the simulation that clearly appears through the camera. That part of the leaf is "gone", yet the energy field of that shape is still there. See video below: 👉 The Phantom Leaf in Kirlian Photography. The phantom part of the leaf is the plasma body, or 'ghost' energy field, and the physical leaf is merely a holographic expression of what the thing should appear as. These two things, while totally integrated normally, are not dependent on each other to still exist. Ghosts that are disembodied still have their energetic light body essence; they just can't assemble the 'physical' part of it anymore. So they can't touch things, taste things, or experience life, all they can do now is watch it around them. That is, unless they go to the astral fields where they can materialize there, but those are artificial worlds the invader races have set up as honeypot traps for the disembodied to now produce loosh for them, just as they are doing to manifest beings here in the looking glass simulation. You built this simulation called a time matrix. Other fractals of your collective of Prime Creator (you can think of as bratty siblings) came along and set up a new simulation nested within this 'organic' one in order to trick you so they can harvest your energy. This is in the way of your light body power, as well as in using you to funnel vast wealth to them through taxes, taxes and more taxes. They also eat your kids (more taxes). The way the hologram is actually projected around you is through projector lenses we call our eyes we think allow us to ‘see’. In reality it is our pineal gland that sees and our eyes merely project our inclusion into the shared reality scape before us so others can see us. And while that might seem impossible to understand, this is how anything within the simulation materializes. Eyes are not camera lenses as touched on above. The optical lenses that stack up inside the pupil are the same convex-to-concave as projection lenses are arranged. They literally cannot 'see' something, they can only project images. In quantum science experiments, such as the Double Slit, it is proven that the aether does not materialize before you the simulation of molecular 'matter' unless the scientist is looking at the experiment. Then that experiment only functions according to the preconception of that particular scientist. The same test run by two different people reveals two different actions. That's because these are two different realities. Yours and theirs. We all live in our own unique worlds, and agree on things like 'leaves are green'. But in reality, my green might be your purple. It is a shared reality field made up of different but complimentary worlds. How you really see is through the 3rd eye pineal gland as mentioned earlier. Naturally the ancients knew this eons ago -now engraved, painted and depicted all across ancient Egypt-. It has the clear ability to see 360 degrees around you what it is you expect to see in that precise spot on earth because the spacetime fabric is holding the colors, shapes and outlines of every leaf and tree and blade of grass that is supposed to be "there" according to all the other people around you that are projecting the same image in the same designated spot, and because you are now looking in that direction, you can see it. Your pineal gland now sends that live image down to your heart with your own body now blended into that same picture where you weren't previously standing, because you don't actually have a body to 'stand' anywhere. The heart hears that signal, then reduces it to a song that pulsates out to all the aether microcrystals around you and suddenly your image will be imprinted or outlined in the air where the spacetime fabric holds your plasma field. The aether particles that hold this shape in the spacetime fabric are called X and Y bosons (also called W and Z bosons, depending on the white paper) that hold the square points within each pixel of the 'fabric' that Higgs bosons now light up according to where that leaf is supposed to be. The Higgs boson is YOUR projected holographic beam. At the same time your pineal gland sends the signal to the heart to alert the aether to your 'reality' of joining the shared reality field, now it also sends a signal through your optic nerve (optic fiber) that connects in a 45 degree angle from your pineal gland to your projector lenses and completes the 'solid' image of your body inside the spacetime fabric halo that's already there thanks to your heart. You are the Higgs boson science calls the god particle. What your eyes cast out before you is merely the holographic insertion of your own body as it interacts within the projection, making it seem like a solid, material version of your body now walking, and interacting with, the rest of the projected holograms as displayed by the spacetime fabric. In case you didn’t think the spacetime fabric is a ‘real’ thing, here is actual photographs taken of our invisible projector screens by scientists at CERN. Just because this is advanced holographic technology doesn't mean it cannot possibly work in such an unheard-of way. Remember, the spacetime fabric has to be triangulated, just like 3D holographic projections, in order for it to show you a fluid, 3D moving image. That triangulation is the X vector boson, the Y gauge boson and you, the Higgs boson. Three points of consciousness working together to project or 'insert' you into the holodeck. Like you, each fractal of Prime Creator around you are all projecting themselves into that shared field, so it makes it feel like this is a real-time, physical, place. But if you ask quantum physics if a falling tree makes a sound in the forest but no one is around to hear it, they will tell you not only does it not make a sound, the forest literally does not exist until a sentient being casts it into reality. The same can be said about you. Unless you are walking down that sidewalk, your shoes aren’t clicking, making a sound as your heels hit the pavement. Plus the pavement won’t even be there if you don’t project it into reality and no one else is around. You will learn that science takes an adamant stance that there is no such thing as static matter. All things blink on and off at a super-fast rate that cannot be detected by the eye. This is the cadence of the spacetime fabric known as the FLASHLINE SEQUENCE that operates on a shared ‘drum beat’ to keep the simulation harmonically tuned we call the Schumann Resonance, 7.83Hz rhythm. When you intend to ‘walk’, you flash onto one spacetime fabric screen, you flash off for a brief moment, then a few inches ahead of where you just were, you flash on a 'forward' screen, giving the illusion you are traveling. The fire plug isn’t moving, so it appears like you are walking past it, giving you the sensation of actually walking from A to B. Each pixel of each spacetime fabric, sandwiched on top of each other as many as millions of sheets per inch, have a vector or IP address within the simulation. So the X and Y bosons holding the space of that pixel can be triangulated by scalar positioning by a scientist from anywhere in the world. Every vector and gauge boson and every pixel can be mapped from any other point within the simulation. We have those IP addresses, and when a time craft wants to go somewhere else, their destination is one of those pixels that will act as the zero point of the craft where it will suddenly appear next. Like you, the craft never moves, it simply resonates with a different vibration that is ‘over there’. But like your video screen you’re looking at now, all things exist on the same sheet of glass, depending on which spacetime fabric you want to see. YOU cast yourself onto the spacetime fabric, otherwise your holographic ‘body’ simply doesn’t exist. And THAT is done by your intent. That is why you can manifest any reality you want to see, as described in ‘The Secret’. If you WANT to see a different, or better reality, you merely have to think of that reality until you find yourself there. For more on this topic, see my articles: 👉 MANIFESTING YOUR GOALS 👉 CASTING THE APOCOLYPSE 👉 CASTING A BETTER REALITY On X, to search for my articles, simply type in the name of the piece, enter one space, then from: & my username in parenthesis such as shown here: MANIFESTING YOUR GOALS (from:iontecs_pemf) Off-site, you can look up any of my writings by through this link below for my other more than 100 recent articles and many thousands of comments on X, regularly updated thanks to Justin This message will only be seen by your eyes if not shared, and if you want to reference this article again later, you will need to cut and paste it in your own notes off line, as it will surely be erased. This is the most accurate translation of these events I am aware of at this time.
3:04

HOW THE HOLOGRAPHIC SIMULATION WORKS (Update 12/11/24) Your ‘reality’ is a holographic projection that comes from your own eyes that are not like camera lenses, but literally projection lenses. How it works is complex, but here is the actual science. There is no such thing as material matter. It takes energy to cast something into fully visible 'solid' form (still a hologram). So as shown in Kirlian photography (spectrography) that shows the aura of things, you can see that even if you cut part of a leaf away, there is still an energy you normally won't see with your eyes that casts out the 'solid' form of that thing within the simulation that clearly appears through the camera. That part of the leaf is "gone", yet the energy field of that shape is still there. See video below: 👉 The Phantom Leaf in Kirlian Photography. The phantom part of the leaf is the plasma body, or 'ghost' energy field, and the physical leaf is merely a holographic expression of what the thing should appear as. These two things, while totally integrated normally, are not dependent on each other to still exist. Ghosts that are disembodied still have their energetic light body essence; they just can't assemble the 'physical' part of it anymore. So they can't touch things, taste things, or experience life, all they can do now is watch it around them. That is, unless they go to the astral fields where they can materialize there, but those are artificial worlds the invader races have set up as honeypot traps for the disembodied to now produce loosh for them, just as they are doing to manifest beings here in the looking glass simulation. You built this simulation called a time matrix. Other fractals of your collective of Prime Creator (you can think of as bratty siblings) came along and set up a new simulation nested within this 'organic' one in order to trick you so they can harvest your energy. This is in the way of your light body power, as well as in using you to funnel vast wealth to them through taxes, taxes and more taxes. They also eat your kids (more taxes). The way the hologram is actually projected around you is through projector lenses we call our eyes we think allow us to ‘see’. In reality it is our pineal gland that sees and our eyes merely project our inclusion into the shared reality scape before us so others can see us. And while that might seem impossible to understand, this is how anything within the simulation materializes. Eyes are not camera lenses as touched on above. The optical lenses that stack up inside the pupil are the same convex-to-concave as projection lenses are arranged. They literally cannot 'see' something, they can only project images. In quantum science experiments, such as the Double Slit, it is proven that the aether does not materialize before you the simulation of molecular 'matter' unless the scientist is looking at the experiment. Then that experiment only functions according to the preconception of that particular scientist. The same test run by two different people reveals two different actions. That's because these are two different realities. Yours and theirs. We all live in our own unique worlds, and agree on things like 'leaves are green'. But in reality, my green might be your purple. It is a shared reality field made up of different but complimentary worlds. How you really see is through the 3rd eye pineal gland as mentioned earlier. Naturally the ancients knew this eons ago -now engraved, painted and depicted all across ancient Egypt-. It has the clear ability to see 360 degrees around you what it is you expect to see in that precise spot on earth because the spacetime fabric is holding the colors, shapes and outlines of every leaf and tree and blade of grass that is supposed to be "there" according to all the other people around you that are projecting the same image in the same designated spot, and because you are now looking in that direction, you can see it. Your pineal gland now sends that live image down to your heart with your own body now blended into that same picture where you weren't previously standing, because you don't actually have a body to 'stand' anywhere. The heart hears that signal, then reduces it to a song that pulsates out to all the aether microcrystals around you and suddenly your image will be imprinted or outlined in the air where the spacetime fabric holds your plasma field. The aether particles that hold this shape in the spacetime fabric are called X and Y bosons (also called W and Z bosons, depending on the white paper) that hold the square points within each pixel of the 'fabric' that Higgs bosons now light up according to where that leaf is supposed to be. The Higgs boson is YOUR projected holographic beam. At the same time your pineal gland sends the signal to the heart to alert the aether to your 'reality' of joining the shared reality field, now it also sends a signal through your optic nerve (optic fiber) that connects in a 45 degree angle from your pineal gland to your projector lenses and completes the 'solid' image of your body inside the spacetime fabric halo that's already there thanks to your heart. You are the Higgs boson science calls the god particle. What your eyes cast out before you is merely the holographic insertion of your own body as it interacts within the projection, making it seem like a solid, material version of your body now walking, and interacting with, the rest of the projected holograms as displayed by the spacetime fabric. In case you didn’t think the spacetime fabric is a ‘real’ thing, here is actual photographs taken of our invisible projector screens by scientists at CERN. Just because this is advanced holographic technology doesn't mean it cannot possibly work in such an unheard-of way. Remember, the spacetime fabric has to be triangulated, just like 3D holographic projections, in order for it to show you a fluid, 3D moving image. That triangulation is the X vector boson, the Y gauge boson and you, the Higgs boson. Three points of consciousness working together to project or 'insert' you into the holodeck. Like you, each fractal of Prime Creator around you are all projecting themselves into that shared field, so it makes it feel like this is a real-time, physical, place. But if you ask quantum physics if a falling tree makes a sound in the forest but no one is around to hear it, they will tell you not only does it not make a sound, the forest literally does not exist until a sentient being casts it into reality. The same can be said about you. Unless you are walking down that sidewalk, your shoes aren’t clicking, making a sound as your heels hit the pavement. Plus the pavement won’t even be there if you don’t project it into reality and no one else is around. You will learn that science takes an adamant stance that there is no such thing as static matter. All things blink on and off at a super-fast rate that cannot be detected by the eye. This is the cadence of the spacetime fabric known as the FLASHLINE SEQUENCE that operates on a shared ‘drum beat’ to keep the simulation harmonically tuned we call the Schumann Resonance, 7.83Hz rhythm. When you intend to ‘walk’, you flash onto one spacetime fabric screen, you flash off for a brief moment, then a few inches ahead of where you just were, you flash on a 'forward' screen, giving the illusion you are traveling. The fire plug isn’t moving, so it appears like you are walking past it, giving you the sensation of actually walking from A to B. Each pixel of each spacetime fabric, sandwiched on top of each other as many as millions of sheets per inch, have a vector or IP address within the simulation. So the X and Y bosons holding the space of that pixel can be triangulated by scalar positioning by a scientist from anywhere in the world. Every vector and gauge boson and every pixel can be mapped from any other point within the simulation. We have those IP addresses, and when a time craft wants to go somewhere else, their destination is one of those pixels that will act as the zero point of the craft where it will suddenly appear next. Like you, the craft never moves, it simply resonates with a different vibration that is ‘over there’. But like your video screen you’re looking at now, all things exist on the same sheet of glass, depending on which spacetime fabric you want to see. YOU cast yourself onto the spacetime fabric, otherwise your holographic ‘body’ simply doesn’t exist. And THAT is done by your intent. That is why you can manifest any reality you want to see, as described in ‘The Secret’. If you WANT to see a different, or better reality, you merely have to think of that reality until you find yourself there. For more on this topic, see my articles: 👉 MANIFESTING YOUR GOALS 👉 CASTING THE APOCOLYPSE 👉 CASTING A BETTER REALITY On X, to search for my articles, simply type in the name of the piece, enter one space, then from: & my username in parenthesis such as shown here: MANIFESTING YOUR GOALS (from:iontecs_pemf) Off-site, you can look up any of my writings by through this link below for my other more than 100 recent articles and many thousands of comments on X, regularly updated thanks to Justin This message will only be seen by your eyes if not shared, and if you want to reference this article again later, you will need to cut and paste it in your own notes off line, as it will surely be erased. This is the most accurate translation of these events I am aware of at this time.

W.R. Schock, QBD

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