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Extract TEXT only from Cell in Microsoft #Excel 365 Version =TEXTJOIN(" ",,TEXTSPLIT(B5,TEXTSPLIT(B5,CHAR(SEQUENCE(,26,65)),,1,1),,1)) Thanks to Rick Rothstein (LINKEDIN) for Solution

Excel Basement

33,750 subscribers

14,474 次观看 • 2 年前 •via X (Twitter)

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@av2 年前

Boss can u pls help me for this 123.45MBPS Or 188 KBPs So some times it is with space sometimes it is without. And I will need number part different and text part different

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Count / Sum Multiple Values in a Cell (Excel 365 Version) =COUNT(--TEXTSPLIT(MID(B5,2,LEN(B5)-2),{",","&"})) =SUM(--TEXTSPLIT(MID(B10,2,LEN(B10)-2),{",","&"})) =COUNTA(--TEXTSPLIT(MID(B14,2,LEN(B14)-2),{",","&"}))

Count / Sum Multiple Values in a Cell (Excel 365 Version) =COUNT(--TEXTSPLIT(MID(B5,2,LEN(B5)-2),{",","&"})) =SUM(--TEXTSPLIT(MID(B10,2,LEN(B10)-2),{",","&"})) =COUNTA(--TEXTSPLIT(MID(B14,2,LEN(B14)-2),{",","&"}))

Excel Basement

23,102 次观看 • 2 年前

MICROSOFT REJECTED THIS GUY SO HE VIBE CODED HIS OWN EXCEL applied to microsoft, got rejected, decided to build a terminal-based spreadsheet viewer from scratch here's what it actually does: > opens and renders .xlsx and .csv files directly in your terminal > keyboard-driven navigation so you never touch a mouse > handles large datasets without the lag that modern excel has > cell formatting, formulas, and sorting all working in the CLI > lightweight enough to run on any machine instantly no ribbon UI, no bloat, no web version that takes 10 seconds to load just a fast spreadsheet tool that looks like something from the 80s but performs better than most modern alternatives the first user, who was a data analyst, said he's been complaining for years that the move to ribbon was a punch to the face for hardcore users another user said it reminds them of lotus 1-2-3 from the DOS days but way slicker modern excel is 90% features nobody uses and 10% of what power users actually need this guy stripped it down to the 10% and made it fast

MICROSOFT REJECTED THIS GUY SO HE VIBE CODED HIS OWN EXCEL applied to microsoft, got rejected, decided to build a terminal-based spreadsheet viewer from scratch here's what it actually does: > opens and renders .xlsx and .csv files directly in your terminal > keyboard-driven navigation so you never touch a mouse > handles large datasets without the lag that modern excel has > cell formatting, formulas, and sorting all working in the CLI > lightweight enough to run on any machine instantly no ribbon UI, no bloat, no web version that takes 10 seconds to load just a fast spreadsheet tool that looks like something from the 80s but performs better than most modern alternatives the first user, who was a data analyst, said he's been complaining for years that the move to ribbon was a punch to the face for hardcore users another user said it reminds them of lotus 1-2-3 from the DOS days but way slicker modern excel is 90% features nobody uses and 10% of what power users actually need this guy stripped it down to the 10% and made it fast

Om Patel

86,946 次观看 • 3 个月前

MICROSOFT QUIETLY SHIPPED THE RAG PIPELINE EVERYONE KEEPS TRYING TO BUILD FROM SCRATCH it is called Kernel Memory, and it turns any pile of files into an AI memory that answers with citations. drop your data in and Microsoft's pipeline does the rest: > ingest PDFs, Word, PPT, Excel, web pages, even images > extract the text, chunk it, embed it into vectors > store the vectors with metadata and keep the originals in blob storage > ask a question and it pulls the right chunks with semantic plus hybrid search then it hands the answer back grounded, with links to the exact source and full token usage. and it plugs into whatever you already run: > Azure OpenAI, OpenAI, Ollama, or Anthropic for the models > Qdrant, pgvector, Redis, or Azure AI Search for the vectors > every step is a swappable handler, so you can replace any part with your own one heads up: Microsoft archived the repo in June 2026 and ships it as a reference blueprint, not production. but as a map for how memory and RAG are actually built, nothing is cleaner. run it in one command: docker run kernelmemory/service bookmark this. Microsoft already drew the blueprint, you just build on it.

MICROSOFT QUIETLY SHIPPED THE RAG PIPELINE EVERYONE KEEPS TRYING TO BUILD FROM SCRATCH it is called Kernel Memory, and it turns any pile of files into an AI memory that answers with citations. drop your data in and Microsoft's pipeline does the rest: > ingest PDFs, Word, PPT, Excel, web pages, even images > extract the text, chunk it, embed it into vectors > store the vectors with metadata and keep the originals in blob storage > ask a question and it pulls the right chunks with semantic plus hybrid search then it hands the answer back grounded, with links to the exact source and full token usage. and it plugs into whatever you already run: > Azure OpenAI, OpenAI, Ollama, or Anthropic for the models > Qdrant, pgvector, Redis, or Azure AI Search for the vectors > every step is a swappable handler, so you can replace any part with your own one heads up: Microsoft archived the repo in June 2026 and ships it as a reference blueprint, not production. but as a map for how memory and RAG are actually built, nothing is cleaner. run it in one command: docker run kernelmemory/service bookmark this. Microsoft already drew the blueprint, you just build on it.

NO1ennn

85,010 次观看 • 17 天前

Microsoft spent $13 billion and 3 years building an AI that knows your work context. Every time you open it, it still asks what you're working on. This developer set up a plain text file in 2 minutes. The file is called CLAUDE.md. It loads before every session. Before he types a single word. It already knows his name. It already knows his writing style. It already knows what he's building, who it's for, and what he never wants to see in a response. He doesn't introduce himself anymore. He doesn't explain his preferences anymore. He doesn't correct the same mistakes twice. He just works. No $30/month Copilot subscription. No Microsoft 365. No IT approval. No data sharing agreement. No onboarding. Just a plain text file, a free text editor, and 21 instructions a developer distilled from Andrej Karpathy's research. Those 21 instructions moved Claude's coding accuracy from 65% to 94%. The file hit #1 on GitHub with 82,000 stars. Most people using Claude right now have never heard of it. Microsoft has 221,000 employees, $13 billion invested in OpenAI, and a direct integration into every Windows laptop sold on the planet.. they built an AI assistant most companies pay $30/user/month for that still doesn't know your name. This developer has a laptop, a text file and a 2-minute setup.. he built something that knows more about how he works than any enterprise AI on the market. The $50 billion AI personalization industry just got embarrassed by a .md file. full breakdown down below

Microsoft spent $13 billion and 3 years building an AI that knows your work context. Every time you open it, it still asks what you're working on. This developer set up a plain text file in 2 minutes. The file is called CLAUDE.md. It loads before every session. Before he types a single word. It already knows his name. It already knows his writing style. It already knows what he's building, who it's for, and what he never wants to see in a response. He doesn't introduce himself anymore. He doesn't explain his preferences anymore. He doesn't correct the same mistakes twice. He just works. No $30/month Copilot subscription. No Microsoft 365. No IT approval. No data sharing agreement. No onboarding. Just a plain text file, a free text editor, and 21 instructions a developer distilled from Andrej Karpathy's research. Those 21 instructions moved Claude's coding accuracy from 65% to 94%. The file hit #1 on GitHub with 82,000 stars. Most people using Claude right now have never heard of it. Microsoft has 221,000 employees, $13 billion invested in OpenAI, and a direct integration into every Windows laptop sold on the planet.. they built an AI assistant most companies pay $30/user/month for that still doesn't know your name. This developer has a laptop, a text file and a 2-minute setup.. he built something that knows more about how he works than any enterprise AI on the market. The $50 billion AI personalization industry just got embarrassed by a .md file. full breakdown down below

Dep

14,117 次观看 • 4 个月前

⚡️We are excited to announce that our new no-code Enterprise Platform is NOW available in private beta! As RAG apps advance from prototype to production we’ve been overwhelmed by requests for an enterprise grade solution to provide these applications with the data they need. Designed to make it easy to get your data #RAGready, our Platform can preprocess more than 25 file types and soon will be fully #multimodal, also able to ingest audio, video and image files. We ship with a baseline suite of source connectors, including Amazon Web Services S3, Microsoft Azure Blob Storage, OneDrive, SFTP, Databricks Delta Table, Google Drive, Salesforce, Elastic, OpenSearch, and Google Cloud storage with many more fast following. Platform transforms your documents into a standardized JSON schema, broken down into semantically coherent elements allowing you to reconstruct your document in the manner most useful to you. Want only the narrative text but not the headers and footers? This is entirely configurable through the UI. Additionally, we generate more than 30 types of metadata for each element to make it easy to curate the data being written downstream and to support metadata filtering during retrieval. Smart chunking and the ability to choose from a range of embedding models are in from launch, delivering a turnkey solution for chunk and embedding experimentation. As for destination connectors, we've got that covered too, with Amazon Web Services S3, Pinecone, Chroma , Weaviate AI Database, Google Cloud storage, MongoDB, Microsoft Azure cognitive search, PostgreSQL, Elastic, OpenSearch, and Databricks Delta Table. And of course, all of this can be scheduled to keep your data continuously hydrated. The private-beta is live today! Sign-up to get access and come build the future of LLM data foundations with us: 🚀 #ETLforLLMs #AI #DataPreprocessing #DataScience #DataTransformation #LLMs #ETL #ML #PreppingData #MachineLearning #RAG #Engineer #Unstructured #Unstructuredio #RetrievalAugmentedGeneration #multimodal #AIJobs

⚡️We are excited to announce that our new no-code Enterprise Platform is NOW available in private beta! As RAG apps advance from prototype to production we’ve been overwhelmed by requests for an enterprise grade solution to provide these applications with the data they need. Designed to make it easy to get your data #RAGready, our Platform can preprocess more than 25 file types and soon will be fully #multimodal, also able to ingest audio, video and image files. We ship with a baseline suite of source connectors, including Amazon Web Services S3, Microsoft Azure Blob Storage, OneDrive, SFTP, Databricks Delta Table, Google Drive, Salesforce, Elastic, OpenSearch, and Google Cloud storage with many more fast following. Platform transforms your documents into a standardized JSON schema, broken down into semantically coherent elements allowing you to reconstruct your document in the manner most useful to you. Want only the narrative text but not the headers and footers? This is entirely configurable through the UI. Additionally, we generate more than 30 types of metadata for each element to make it easy to curate the data being written downstream and to support metadata filtering during retrieval. Smart chunking and the ability to choose from a range of embedding models are in from launch, delivering a turnkey solution for chunk and embedding experimentation. As for destination connectors, we've got that covered too, with Amazon Web Services S3, Pinecone, Chroma , Weaviate AI Database, Google Cloud storage, MongoDB, Microsoft Azure cognitive search, PostgreSQL, Elastic, OpenSearch, and Databricks Delta Table. And of course, all of this can be scheduled to keep your data continuously hydrated. The private-beta is live today! Sign-up to get access and come build the future of LLM data foundations with us: 🚀 #ETLforLLMs #AI #DataPreprocessing #DataScience #DataTransformation #LLMs #ETL #ML #PreppingData #MachineLearning #RAG #Engineer #Unstructured #Unstructuredio #RetrievalAugmentedGeneration #multimodal #AIJobs

Unstructured

21,909 次观看 • 2 年前

Miles Guo ft. WarRoom on April 18, 2020: America is facing a disastrous time. Only by acquiring the correct information can America find the right solution to this CCP biological warfare. He delivered the messages: 1. The COVID-19 virus was man-made and came from the P4 lab. It was created as a biological weapon from the very beginning. 🔺 Since 2016, CCP/PLA-affiliated military media, CCTV 7, had repeatedly discussed the CCP’s biological weapons program and its capability to defeat America with the low-cost bioweapon. 🔺 One of the purposes was to destroy America, damage its economy, and ultimately force the U.S. to kowtow to and seek help from Xi Jinping and Wang Qishan. 2. American government agencies, including intelligence agencies, failed to obtain accurate information. 🔺 America could not respond properly without accurate intelligence about China and the virus. 🔺 The CCP did not provide correct information to the U.S., while the U.S. had wrong or incomplete intelligence about the CCP. 🔺 Whistleblowers inside the CCP were providing information to the Whistleblower Movement and tried to convey the accurate information to save lives. 3. Of 2,000 evidentiary images, one of them illustrated that the CCP changed its genetic sequence report three times in a row. 🔺 Jan. 12, 2020: The CCP sent the NIH information concerning the genetic sequence of the Wuhan coronavirus. 🔺 Jan. 14: The sequence was changed. 🔺 Jan. 17: It was changed for a third time. The three entries were completely different. U.S. intelligence agencies and relevant government agencies need to investigate why the genetic sequence was changed three times—and why the entries were completely different. America is facing a disastrous time. Only by acquiring the correct information, can the country found the right solution to this biological warfare.

Miles Guo ft. WarRoom on April 18, 2020: America is facing a disastrous time. Only by acquiring the correct information can America find the right solution to this CCP biological warfare. He delivered the messages: 1. The COVID-19 virus was man-made and came from the P4 lab. It was created as a biological weapon from the very beginning. 🔺 Since 2016, CCP/PLA-affiliated military media, CCTV 7, had repeatedly discussed the CCP’s biological weapons program and its capability to defeat America with the low-cost bioweapon. 🔺 One of the purposes was to destroy America, damage its economy, and ultimately force the U.S. to kowtow to and seek help from Xi Jinping and Wang Qishan. 2. American government agencies, including intelligence agencies, failed to obtain accurate information. 🔺 America could not respond properly without accurate intelligence about China and the virus. 🔺 The CCP did not provide correct information to the U.S., while the U.S. had wrong or incomplete intelligence about the CCP. 🔺 Whistleblowers inside the CCP were providing information to the Whistleblower Movement and tried to convey the accurate information to save lives. 3. Of 2,000 evidentiary images, one of them illustrated that the CCP changed its genetic sequence report three times in a row. 🔺 Jan. 12, 2020: The CCP sent the NIH information concerning the genetic sequence of the Wuhan coronavirus. 🔺 Jan. 14: The sequence was changed. 🔺 Jan. 17: It was changed for a third time. The three entries were completely different. U.S. intelligence agencies and relevant government agencies need to investigate why the genetic sequence was changed three times—and why the entries were completely different. America is facing a disastrous time. Only by acquiring the correct information, can the country found the right solution to this biological warfare.

Rica

13,551 次观看 • 1 个月前

Finally new version of text system is released on our website ! I released as update to old version but in reality it's completely new thing in material and lot's of work in verse. I'm still working on documentation or/and videos but here is a list of good stuff it does: - Material got much lighter as slots logic moved to vertex shader. - Characters can overlap and still won't be cut out compared to old version. - Character can be animated and I already implemented some (wave, scale up/down and shake). - Custom face camera logic which works with prop scale so no need to additionally specify with and height. - Rows offset automatically when scale up or down any row. - Text effects now can be applied to any character, so words or single character. - Custom glint which works perfectly with any number of rows as a single line with multiple important controls. - Higher quality outline with two parameters to control inner and outer edge. - Timer logic split into to parts, verse and material. Verse setup initial layout and reserve slots for timer digits and then each second just sends seconds value and GPU makes timer tick freeing verse TPS by huge number. - To apply effects simply need use parsing markup with custom tag where N number between 1-9. So simply can write " Hello World" and word Hello will have rainbow effect applied. Currently implemented 4 effects. - To use icons in slots from texture array is as simple as specify another tag [iconN] where N is number of icon in array. So for example if coin is icon index 0 just need to write [icon1]100K. - Progress bar is supported as well and can be snapped to row without eyeball offset. - Background image supported now too! In the video yellow one is as test and you can use any of your own. Verse side got lots of changes: - Now saves/caches layouts better. - Smart packing of data allowed drastically reduce number of parameters, which should help with network optimization! - Instead having vector parameter per each slot to just send character index and position (32x5=160 if used 5 rows) now it's only 11 vector parameters per each row so 11x5=55 which is huge save and it sends text effects index in it too! - Implemented text update queue for text which doesn't require instant update. It helps to give more breathing for other text props which needs that speed. - Materials code now use interface and wrappers for cleaner work. If you still read it then thank you! :) On our website we now run 25% sale! And if you own old version please DM me here or in Discord and I will give you promo code for 100% discount on our website! Gelos Games Fortnite #uefn #EpicPartner

Finally new version of text system is released on our website ! I released as update to old version but in reality it's completely new thing in material and lot's of work in verse. I'm still working on documentation or/and videos but here is a list of good stuff it does: - Material got much lighter as slots logic moved to vertex shader. - Characters can overlap and still won't be cut out compared to old version. - Character can be animated and I already implemented some (wave, scale up/down and shake). - Custom face camera logic which works with prop scale so no need to additionally specify with and height. - Rows offset automatically when scale up or down any row. - Text effects now can be applied to any character, so words or single character. - Custom glint which works perfectly with any number of rows as a single line with multiple important controls. - Higher quality outline with two parameters to control inner and outer edge. - Timer logic split into to parts, verse and material. Verse setup initial layout and reserve slots for timer digits and then each second just sends seconds value and GPU makes timer tick freeing verse TPS by huge number. - To apply effects simply need use parsing markup with custom tag where N number between 1-9. So simply can write " Hello World" and word Hello will have rainbow effect applied. Currently implemented 4 effects. - To use icons in slots from texture array is as simple as specify another tag [iconN] where N is number of icon in array. So for example if coin is icon index 0 just need to write [icon1]100K. - Progress bar is supported as well and can be snapped to row without eyeball offset. - Background image supported now too! In the video yellow one is as test and you can use any of your own. Verse side got lots of changes: - Now saves/caches layouts better. - Smart packing of data allowed drastically reduce number of parameters, which should help with network optimization! - Instead having vector parameter per each slot to just send character index and position (32x5=160 if used 5 rows) now it's only 11 vector parameters per each row so 11x5=55 which is huge save and it sends text effects index in it too! - Implemented text update queue for text which doesn't require instant update. It helps to give more breathing for other text props which needs that speed. - Materials code now use interface and wrappers for cleaner work. If you still read it then thank you! :) On our website we now run 25% sale! And if you own old version please DM me here or in Discord and I will give you promo code for 100% discount on our website! Gelos Games Fortnite #uefn #EpicPartner

AsicsoN

13,192 次观看 • 3 个月前

My New Market Dashboard Inspired by Jeff Jeff Sun, CFTe and Clement Ang , I originally used Excel to design my own market dashboard for tracking sectors, industries, and country ETFs. However, with recent advancements in AI-assisted coding, I’ve found that an HTML-based version is not only more aesthetic but also far more powerful. It allows for advanced features like calculating ATR multiple extensions from the 50D SMA and Volatility Adjusted Relative Strength. I’ve also integrated TradingView charts and a section for tracking macro events directly on the page. I’m now sharing this dashboard with FinTwit community. If you aren’t interested in the code, you can simply view the static page after 16:30 ET, as it is automatically updated via GitHub. If you’d like to customize it, the source code is open-source and available for you to modify. Thanks for your support! Features: • Indices, sectors, industries, country ETFs • ATR%, ATR multiple extension from 50SMA, 1M-VARS (volatility-adjusted relative strength) • Macro events calendar • TradingView charts • Auto-refresh Mon–Fri 16:30 ET via GitHub Actions • Data: Yahoo Finance + investpy Live site (no setup): Source code:

My New Market Dashboard Inspired by Jeff Jeff Sun, CFTe and Clement Ang , I originally used Excel to design my own market dashboard for tracking sectors, industries, and country ETFs. However, with recent advancements in AI-assisted coding, I’ve found that an HTML-based version is not only more aesthetic but also far more powerful. It allows for advanced features like calculating ATR multiple extensions from the 50D SMA and Volatility Adjusted Relative Strength. I’ve also integrated TradingView charts and a section for tracking macro events directly on the page. I’m now sharing this dashboard with FinTwit community. If you aren’t interested in the code, you can simply view the static page after 16:30 ET, as it is automatically updated via GitHub. If you’d like to customize it, the source code is open-source and available for you to modify. Thanks for your support! Features: • Indices, sectors, industries, country ETFs • ATR%, ATR multiple extension from 50SMA, 1M-VARS (volatility-adjusted relative strength) • Macro events calendar • TradingView charts • Auto-refresh Mon–Fri 16:30 ET via GitHub Actions • Data: Yahoo Finance + investpy Live site (no setup): Source code:

Will Hu

152,108 次观看 • 6 个月前

Today, we expand zero-shot drug design beyond binding to the design of multifunctional medicines, the intracellular proteome, and state-of-the-art atomic precision with our model, JAM-2. In a new report (below), we show: 1. The first drug-grade, fully computationally designed multispecific antibodies against five peptide-MHCs: Routine picomolar T-cell activation/cell-killing EC50s, >100-fold selectivity, and drug-like developability 2. The first fully generatively designed, drug-grade dual-variant KRAS G12 multispecifics: They recruit primary T-cells from human donors to kill G12V and G12C presenting cells at pM to single-digit-nM potency, completely sparing wild-type. 3. Atomic accuracy, from sequence alone: Angstrom-level agreement between Cryo-EM and JAM-2 de novo designs, requiring only target sequences (not structure) as input. 4. Unrivaled speed with an AI-native in-house wet lab: Designed, built, and tested five programs in one parallelized campaign, end-to-end in-house in ~6 weeks. 5. A higher validation bar for AI-generated drug candidates: In a field increasingly rife with hype and uneven standards of proof, we provide the highest quality public wet-lab validation of AI-designed antibodies to date. We share experimental methods in full, and invite folks to adopt and build on these standards. Truly individualized therapies will be the most important contribution of AI in drug design. These advances help accelerate this future.

Today, we expand zero-shot drug design beyond binding to the design of multifunctional medicines, the intracellular proteome, and state-of-the-art atomic precision with our model, JAM-2. In a new report (below), we show: 1. The first drug-grade, fully computationally designed multispecific antibodies against five peptide-MHCs: Routine picomolar T-cell activation/cell-killing EC50s, >100-fold selectivity, and drug-like developability 2. The first fully generatively designed, drug-grade dual-variant KRAS G12 multispecifics: They recruit primary T-cells from human donors to kill G12V and G12C presenting cells at pM to single-digit-nM potency, completely sparing wild-type. 3. Atomic accuracy, from sequence alone: Angstrom-level agreement between Cryo-EM and JAM-2 de novo designs, requiring only target sequences (not structure) as input. 4. Unrivaled speed with an AI-native in-house wet lab: Designed, built, and tested five programs in one parallelized campaign, end-to-end in-house in ~6 weeks. 5. A higher validation bar for AI-generated drug candidates: In a field increasingly rife with hype and uneven standards of proof, we provide the highest quality public wet-lab validation of AI-designed antibodies to date. We share experimental methods in full, and invite folks to adopt and build on these standards. Truly individualized therapies will be the most important contribution of AI in drug design. These advances help accelerate this future.

Nabla Bio

179,711 次观看 • 2 个月前

⚙️Update Quick Video Review: GameSir Connect V1.14.4⚙️ GameSir Connect has just been updated to version V1.14.4. Over the past few updates, we have introduced many practical features to enhance your experience. Here is the video detailing all the highlights of the recent updates. We highly recommend that players visit the Microsoft Store to download the latest version from here: For details on the updates, please refer to the text below. ✅Feature 1 - Professional Tips and Explanation for Controller Settings. You can now hover your mouse over the ⓘ icon to access detailed explanations of controller terminology. These tips have been verified by the GameSir product team to ensure you can quickly, conveniently, and accurately understand the information you need. ✅Feature 2 - Enhanced Stick Customization: Expanded Curve & Calibration Settings Now, you can adjust the stick center point to fix any potential center offset after the controller has already been calibrated. In addition, you can now achieve more precise fine-tuning of the stick input curve by manually entering the coordinates for each point within a 100x100 coordinate system. Please be aware that when Zero Deadzone is enabled, it is normal for the center point to not return to absolute zero or for the data to fluctuate repeatedly. ✅Feature 3 - Support for in-app software updates and halved input latency We've now set up a dedicated server for GameSir Connect software updates. Now, you can update directly within the software. And through optimizations, the end-to-end latency for both the G7 Pro 8K PC and Tarantula 8K PC has now reached 0.25ms with the latest firmware. And only by using the latest software will you be able to receive the latest firmware updates.

⚙️Update Quick Video Review: GameSir Connect V1.14.4⚙️ GameSir Connect has just been updated to version V1.14.4. Over the past few updates, we have introduced many practical features to enhance your experience. Here is the video detailing all the highlights of the recent updates. We highly recommend that players visit the Microsoft Store to download the latest version from here: For details on the updates, please refer to the text below. ✅Feature 1 - Professional Tips and Explanation for Controller Settings. You can now hover your mouse over the ⓘ icon to access detailed explanations of controller terminology. These tips have been verified by the GameSir product team to ensure you can quickly, conveniently, and accurately understand the information you need. ✅Feature 2 - Enhanced Stick Customization: Expanded Curve & Calibration Settings Now, you can adjust the stick center point to fix any potential center offset after the controller has already been calibrated. In addition, you can now achieve more precise fine-tuning of the stick input curve by manually entering the coordinates for each point within a 100x100 coordinate system. Please be aware that when Zero Deadzone is enabled, it is normal for the center point to not return to absolute zero or for the data to fluctuate repeatedly. ✅Feature 3 - Support for in-app software updates and halved input latency We've now set up a dedicated server for GameSir Connect software updates. Now, you can update directly within the software. And through optimizations, the end-to-end latency for both the G7 Pro 8K PC and Tarantula 8K PC has now reached 0.25ms with the latest firmware. And only by using the latest software will you be able to receive the latest firmware updates.

GameSir

29,311 次观看 • 1 个月前

Yann LeCun (Yann LeCun ) beautifully explains how the architecture and principles used to train LLMs can not be extended to teach AI the real-world intelligence. In 1 line: LLMs excel where intelligence equals sequence prediction over symbols. Real-world intelligence requires learned world models, abstraction, causality, and action planning under uncertainty, which current next-token training does not provide. He says current LLMs learn by predicting the next token. That objective works very well when the task itself can be reduced to manipulating discrete symbols and sequences. Math, physics problem solving on paper, and coding fit this pattern because success largely comes from searching and composing the right sequences of symbols, equations, or program tokens. With enough data and scale, these models get very good at that kind of structured sequence prediction. Real-world intelligence is different. The physical world is continuous, noisy, uncertain, and high dimensional. To act in it, a system needs internal models that capture objects, dynamics, causality, constraints from the body, and the outcomes of actions over time. Humans and animals build abstract representations from rich sensory streams, then make predictions in that abstract space, not at the raw pixel level. That is why a child can learn intuitive physics, plan multi-step actions, and adapt quickly in new situations with little data. His claim about saturation follows from this gap. Scaling token prediction keeps improving symbol manipulation tasks like math and code, but it hits limits on embodied reasoning and common sense because text alone does not provide the right learning signals for world models. Predicting the next word cannot efficiently teach contact forces, affordances, occlusion, friction, or how actions change the state of the environment. For that, he argues we need architectures that learn abstractions from sensory data and predict futures in abstract latent spaces, then use those predictions to plan actions toward goals with built-in guardrails. --- From 'Pioneer Works' YT Channel (link in comment)

Yann LeCun (Yann LeCun ) beautifully explains how the architecture and principles used to train LLMs can not be extended to teach AI the real-world intelligence. In 1 line: LLMs excel where intelligence equals sequence prediction over symbols. Real-world intelligence requires learned world models, abstraction, causality, and action planning under uncertainty, which current next-token training does not provide. He says current LLMs learn by predicting the next token. That objective works very well when the task itself can be reduced to manipulating discrete symbols and sequences. Math, physics problem solving on paper, and coding fit this pattern because success largely comes from searching and composing the right sequences of symbols, equations, or program tokens. With enough data and scale, these models get very good at that kind of structured sequence prediction. Real-world intelligence is different. The physical world is continuous, noisy, uncertain, and high dimensional. To act in it, a system needs internal models that capture objects, dynamics, causality, constraints from the body, and the outcomes of actions over time. Humans and animals build abstract representations from rich sensory streams, then make predictions in that abstract space, not at the raw pixel level. That is why a child can learn intuitive physics, plan multi-step actions, and adapt quickly in new situations with little data. His claim about saturation follows from this gap. Scaling token prediction keeps improving symbol manipulation tasks like math and code, but it hits limits on embodied reasoning and common sense because text alone does not provide the right learning signals for world models. Predicting the next word cannot efficiently teach contact forces, affordances, occlusion, friction, or how actions change the state of the environment. For that, he argues we need architectures that learn abstractions from sensory data and predict futures in abstract latent spaces, then use those predictions to plan actions toward goals with built-in guardrails. --- From 'Pioneer Works' YT Channel (link in comment)

Rohan Paul

104,460 次观看 • 8 个月前

🚨ALERT: 50% of Data Centers will NEVER connect to the grid. Half of the data centers announced in the last 24 months will NEVER connect to the grid. Kevin O’Leary said it. The data proves it. While everyone’s chasing “paper capacity,” $CIFR and $IREN are sitting on EXECUTED grid connections that can’t be replicated. Here’s why they’re untouchable: 266 GW of power projects canceled in 2025 alone. That’s 2.4x the cancellations from 2024. Why? Because the U.S. grid is facing a structural deficit that nobody wants to talk about. • Data centers need 18-36 months to build • Grid connections take 5-7 YEARS (sometimes 12) • Interconnection queues in PJM and ERCOT now average 7 years • Average interconnection cost in MISO: $753,116 per MW Translation: You can announce a data center tomorrow. But you CAN’T connect it to power until 2032. The math doesn’t work. The timeline doesn’t work. The physics don’t work. $CIFR - The Fixed-Price Power Moat: Cipher control one of the lowest-cost power portfolios in North America. > Power cost: $0.027/kWh (fixed, long-term PPAs) > Debt: $0 > Portfolio: 2.2 GW across Texas But here’s what everyone’s missing: Their 1-gigawatt Colchis site has a FULLY EXECUTED Direct Connect Agreement with American Electric Power. Not “in the queue.” Not “under study.” EXECUTED. Energization: 2028. While competitors are stuck waiting 7+ years for interconnection approvals, $CIFR already has a Tier 1 grid connection locked in. And they just signed: • $5.5 billion, 15-year lease with AWS for 300 MW • 10-year hosting deal with Google/Fluidstack for 168 MW That’s $8.5 billion in contracted lease payments for AI infrastructure. $IREN - The Microsoft Validation: $IREN didn’t just secure power. They secured the ONLY thing that matters: a hyperscaler willing to pre-pay billions. November 2025: $9.7 billion AI Cloud contract with Microsoft. Let me repeat that. Microsoft PRE-PAID for capacity that doesn’t exist yet. Deal structure: • 200 MW of liquid-cooled AI capacity • $1.94 billion annual recurring revenue (once online) • 20% prepayment to fund $5.8 billion GPU purchase from Dell • Four “Horizon” data centers at their 750 MW Childress campus But the real alpha? Their 2.91 GW portfolio of GRID-CONNECTED power. Not speculative. Not “in the queue.” Connected. Energized. Operating. > Sweetwater 1: 1.4 GW (energization accelerated to April 26) > Childress: 750 MW (operating) > Prince George: 160 MW hydro (23k GPUs for AI) $IREN is scaling to $3.4 billion in AI Cloud ARR by end of 2026 using only 16% of their total power capacity. The Peer Comparison Nobody’s Talking About: Everyone’s excited about $RIOT, $MARA, $CORZ, and $WULF. Here’s the problem: $RIOT: 1.7 GW portfolio, mostly Bitcoin-focused. 25 MW HPC lease with AMD ($311M over 10 years). That’s 1/30th the size of IREN’s Microsoft deal. $MARA: Building “behind-the-meter” natural gas generation to BYPASS the grid entirely. Smart strategy, but they’re starting from scratch. 1.8 GW capacity, mostly mining. $CORZ: $10B+ contract with CoreWeave sounds massive. But they’re CONVERTING old mining infrastructure. Not purpose-built for AI. Currently unprofitable. $WULF: 750 MW at Lake Mariner. Zero-carbon hydro/nuclear. Clean energy story is strong. But only 72.5 MW of HPC capacity by Q2 2025. Meanwhile: • $CIFR has 2.2 GW with executed grid agreements and $8.5B in hyperscaler contracts • $IREN has 2.91 GW of energized capacity and a $9.7B Microsoft deal The Cooling Bottleneck: Secured power means NOTHING without secured cooling. November 2025: CyrusOne data center in Illinois went down for 10 hours because ONE chiller failed. This facility handles TRILLIONS in CME trading volume. Energy, agriculture, crypto derivatives markets frozen globally. Why? Because AI racks now consume 600 kW of power (enough to power 500 homes). A single rack failure creates catastrophic heat buildup. $IREN’s solution: Liquid-cooled infrastructure at all Horizon facilities. $CIFR’s solution: Turnkey air-and-liquid cooling delivery for AWS. Hyperscalers aren’t paying billions for “power connections.” They’re paying for THERMAL RELIABILITY. The Numbers That Matter: > PJM capacity prices: 10x increase from 2024 to 2025 (extreme scarcity signal) > Interconnection costs in Louisiana/Missouri: $900,000+ per MW > $64 billion in U.S. data center projects blocked or delayed in 2024-2025 > 25+ major data center projects canceled in 2025 alone The grid is saturated. The timeline is broken. The infrastructure doesn’t exist. But $CIFR and $IREN? They already own the infrastructure. They already have the grid connections. They already have the hyperscaler contracts. The Bottom Line: > AI demand is doubling every 90 days. > Grid capacity takes 5-7 years to build. > You can’t close that gap with announcements. You close it with EXECUTED agreements and ENERGIZED megawatts. $CIFR: $0.027/kWh power, $8.5B in contracts, 1 GW Tier 1 grid connection $IREN: $9.7B Microsoft deal, 2.91 GW energized portfolio, $3.4B ARR target by 2026. While half the industry fights over interconnection queues, these two are already plugged in. The power crunch isn’t coming. It’s here. And the only winners will be the ones who secured their megawatts BEFORE the grid broke. Bullish $CIFR and $IREN. Note: This is NOT financial advice.

🚨ALERT: 50% of Data Centers will NEVER connect to the grid. Half of the data centers announced in the last 24 months will NEVER connect to the grid. Kevin O’Leary said it. The data proves it. While everyone’s chasing “paper capacity,” $CIFR and $IREN are sitting on EXECUTED grid connections that can’t be replicated. Here’s why they’re untouchable: 266 GW of power projects canceled in 2025 alone. That’s 2.4x the cancellations from 2024. Why? Because the U.S. grid is facing a structural deficit that nobody wants to talk about. • Data centers need 18-36 months to build • Grid connections take 5-7 YEARS (sometimes 12) • Interconnection queues in PJM and ERCOT now average 7 years • Average interconnection cost in MISO: $753,116 per MW Translation: You can announce a data center tomorrow. But you CAN’T connect it to power until 2032. The math doesn’t work. The timeline doesn’t work. The physics don’t work. $CIFR - The Fixed-Price Power Moat: Cipher control one of the lowest-cost power portfolios in North America. > Power cost: $0.027/kWh (fixed, long-term PPAs) > Debt: $0 > Portfolio: 2.2 GW across Texas But here’s what everyone’s missing: Their 1-gigawatt Colchis site has a FULLY EXECUTED Direct Connect Agreement with American Electric Power. Not “in the queue.” Not “under study.” EXECUTED. Energization: 2028. While competitors are stuck waiting 7+ years for interconnection approvals, $CIFR already has a Tier 1 grid connection locked in. And they just signed: • $5.5 billion, 15-year lease with AWS for 300 MW • 10-year hosting deal with Google/Fluidstack for 168 MW That’s $8.5 billion in contracted lease payments for AI infrastructure. $IREN - The Microsoft Validation: $IREN didn’t just secure power. They secured the ONLY thing that matters: a hyperscaler willing to pre-pay billions. November 2025: $9.7 billion AI Cloud contract with Microsoft. Let me repeat that. Microsoft PRE-PAID for capacity that doesn’t exist yet. Deal structure: • 200 MW of liquid-cooled AI capacity • $1.94 billion annual recurring revenue (once online) • 20% prepayment to fund $5.8 billion GPU purchase from Dell • Four “Horizon” data centers at their 750 MW Childress campus But the real alpha? Their 2.91 GW portfolio of GRID-CONNECTED power. Not speculative. Not “in the queue.” Connected. Energized. Operating. > Sweetwater 1: 1.4 GW (energization accelerated to April 26) > Childress: 750 MW (operating) > Prince George: 160 MW hydro (23k GPUs for AI) $IREN is scaling to $3.4 billion in AI Cloud ARR by end of 2026 using only 16% of their total power capacity. The Peer Comparison Nobody’s Talking About: Everyone’s excited about $RIOT, $MARA, $CORZ, and $WULF. Here’s the problem: $RIOT: 1.7 GW portfolio, mostly Bitcoin-focused. 25 MW HPC lease with AMD ($311M over 10 years). That’s 1/30th the size of IREN’s Microsoft deal. $MARA: Building “behind-the-meter” natural gas generation to BYPASS the grid entirely. Smart strategy, but they’re starting from scratch. 1.8 GW capacity, mostly mining. $CORZ: $10B+ contract with CoreWeave sounds massive. But they’re CONVERTING old mining infrastructure. Not purpose-built for AI. Currently unprofitable. $WULF: 750 MW at Lake Mariner. Zero-carbon hydro/nuclear. Clean energy story is strong. But only 72.5 MW of HPC capacity by Q2 2025. Meanwhile: • $CIFR has 2.2 GW with executed grid agreements and $8.5B in hyperscaler contracts • $IREN has 2.91 GW of energized capacity and a $9.7B Microsoft deal The Cooling Bottleneck: Secured power means NOTHING without secured cooling. November 2025: CyrusOne data center in Illinois went down for 10 hours because ONE chiller failed. This facility handles TRILLIONS in CME trading volume. Energy, agriculture, crypto derivatives markets frozen globally. Why? Because AI racks now consume 600 kW of power (enough to power 500 homes). A single rack failure creates catastrophic heat buildup. $IREN’s solution: Liquid-cooled infrastructure at all Horizon facilities. $CIFR’s solution: Turnkey air-and-liquid cooling delivery for AWS. Hyperscalers aren’t paying billions for “power connections.” They’re paying for THERMAL RELIABILITY. The Numbers That Matter: > PJM capacity prices: 10x increase from 2024 to 2025 (extreme scarcity signal) > Interconnection costs in Louisiana/Missouri: $900,000+ per MW > $64 billion in U.S. data center projects blocked or delayed in 2024-2025 > 25+ major data center projects canceled in 2025 alone The grid is saturated. The timeline is broken. The infrastructure doesn’t exist. But $CIFR and $IREN? They already own the infrastructure. They already have the grid connections. They already have the hyperscaler contracts. The Bottom Line: > AI demand is doubling every 90 days. > Grid capacity takes 5-7 years to build. > You can’t close that gap with announcements. You close it with EXECUTED agreements and ENERGIZED megawatts. $CIFR: $0.027/kWh power, $8.5B in contracts, 1 GW Tier 1 grid connection $IREN: $9.7B Microsoft deal, 2.91 GW energized portfolio, $3.4B ARR target by 2026. While half the industry fights over interconnection queues, these two are already plugged in. The power crunch isn’t coming. It’s here. And the only winners will be the ones who secured their megawatts BEFORE the grid broke. Bullish $CIFR and $IREN. Note: This is NOT financial advice.

Black Panther Capital

347,528 次观看 • 7 个月前

#ad Hey, folks! I recently took a cool journey to Wisconsin to check out the one and only Impeckable™ House with James Hardie. Did you know there are 70 million woodpeckers in North America—across 23 species?* Lots of them are in Wisconsin, and they love to peck at wood-based siding—which is why siding from James Hardie is the best solution here. Because in addition to resisting wind, flying debris, rain, moisture, rot, mold, and fire damage, Hardie® siding also holds little appeal to woodpeckers—making it IMPECKABLE™ siding! It’s just another reason to go with James Hardie—America’s No. 1 brand of siding.* Oh, and feast your eyes on this new product line, the TimberHue™ Collection. It has a natural wood-grain look. But if you’re hot for it, you’re gonna have to wait a few months: It’s coming next year. 😊 --- * Partners in Flight Population Estimates Database, Version 3.1, accessed July 18, 2025, Hardie® fiber cement products are noncombustible and/or have a Class A fire rating when tested in accordance with ASTM E84. Fiber cement fire resistance does not extend to applied paints or coatings, which may be damaged or char when exposed to flames. The use of noncombustible siding, combined with other fire mitigation measures, may help harden a home against external fire. * Based on Freedonia 2022 Global Siding (Cladding) demand estimates and James Hardie sales in North America.

Josh Morgerman

16,970 次观看 • 1 年前

WARP SPEED: EPISODE 3 - starring Dada, CEO of Sorce Jobs Dada You only get to live once. So you have to use the best software you can. Dada, daniel ajayi and david built Sorce (YC F25) into Tinder for Jobs—20 million swipes, companies like SpaceX, Anduril, Stripe, DoorDash, and Lyft hiring through their platform. 2.7 million video views. Got into YC three days after the deadline. Dada didn't plan to start a company. He built Sorce to apply to jobs faster for himself. Then SpaceX hired someone through Sorce. Then Anduril did too. "Our biggest fear was: are you just going to destroy the industry? Then Anduril hired someone from Sorce, and SpaceX hired someone from Sorce. I was like, okay, they actually like us." Now Sorce is contributing to the economy: - 20 million swipes in total - Every major tech company has interviewed or hired someone from Sorce - On track to contribute to 1% of all applications in the world - Built the first version in 2-3 weeks, launched the app in 7 weeks - Team of 5 moving at Gabriella Warp Speed In this conversation: (0:00) "I didn't want to start a company. I just wanted to apply to jobs faster" (0:36) Why Y Combinator: Working with world-class people like the founder of Google Photos David Lieb (0:48) The problem: Applying to jobs is painfully repetitive (01:07) Viral launch: 2.7M views—LinkedIn loved it, Twitter said "you're going to destroy the world" (01:45) From 30,000 swipes to 20M: On track for 1% of all applications in the world (02:45) Building the team: 5 people shipping at Warp speed (03:45) Shipping velocity: Built Tinder for Jobs in 7 weeks (04:20) Switching from Rippling: "The UI was very confusing. I paid a contractor twice" (04:33) Switching to Warp: “Warp is a breath of fresh air, it’s like moving from Teams to Slack. The design is just really beautiful” (04:58) Setting the bar: "You want to be inspired by everything you use. It also helps you as a founder to know where the bar is. I’m building a B2B product soon and it should look like Warp and it should be as simple as warp”

WARP SPEED: EPISODE 3 - starring Dada, CEO of Sorce Jobs Dada You only get to live once. So you have to use the best software you can. Dada, daniel ajayi and david built Sorce (YC F25) into Tinder for Jobs—20 million swipes, companies like SpaceX, Anduril, Stripe, DoorDash, and Lyft hiring through their platform. 2.7 million video views. Got into YC three days after the deadline. Dada didn't plan to start a company. He built Sorce to apply to jobs faster for himself. Then SpaceX hired someone through Sorce. Then Anduril did too. "Our biggest fear was: are you just going to destroy the industry? Then Anduril hired someone from Sorce, and SpaceX hired someone from Sorce. I was like, okay, they actually like us." Now Sorce is contributing to the economy: - 20 million swipes in total - Every major tech company has interviewed or hired someone from Sorce - On track to contribute to 1% of all applications in the world - Built the first version in 2-3 weeks, launched the app in 7 weeks - Team of 5 moving at Gabriella Warp Speed In this conversation: (0:00) "I didn't want to start a company. I just wanted to apply to jobs faster" (0:36) Why Y Combinator: Working with world-class people like the founder of Google Photos David Lieb (0:48) The problem: Applying to jobs is painfully repetitive (01:07) Viral launch: 2.7M views—LinkedIn loved it, Twitter said "you're going to destroy the world" (01:45) From 30,000 swipes to 20M: On track for 1% of all applications in the world (02:45) Building the team: 5 people shipping at Warp speed (03:45) Shipping velocity: Built Tinder for Jobs in 7 weeks (04:20) Switching from Rippling: "The UI was very confusing. I paid a contractor twice" (04:33) Switching to Warp: “Warp is a breath of fresh air, it’s like moving from Teams to Slack. The design is just really beautiful” (04:58) Setting the bar: "You want to be inspired by everything you use. It also helps you as a founder to know where the bar is. I’m building a B2B product soon and it should look like Warp and it should be as simple as warp”

Ayush S

20,553 次观看 • 9 个月前

"How to Confirm A Date -- The Day of the Date." I'm not sure what happened to this guy leading up to the date. I don't have the text exchange. But even when he texts her, "I'm on my way to the date" -- that's a little bit of a red flag on this guy's "method." All of which begs the question: How do you confirm a date...the day of the date? Plenty of ways to skin this cat. Here's one: Assuming the time and place are already set... On the afternoon of the date (somewhere between noon and 1 p.m.) Send a soft confirmation text. Do not send: "Hey are we still on for tonight at 7:30 p.m. ? (Needy and clueless). It's hot as fck on the east coast right now. So I'd probably send something like... "Feel like these ice cold margs are gonna hit tonight" I'm painting a picture. It sounds fun and relaxing because hey, who doesn't love drinking a margarita on a hot summer evening. And it subtly cues that it's her turn to confirm. Her: "omg yeh its crazy hot looking fwd to it :)" If she says nothing then you know a flake is likely in the cards. So what do you do? Either way, you do the same thing. Here's what I mean: I always pick a bar walking distance from my place -- so ymmv. But 15 minutes before the date... You text something like, "text when you arrive" It's a vague text but the way it's worded is crucial: If you read closely, it does NOT say nor imply: "I've arrived. So let me know when you've arrived." (Translation: "I'm super eager to meet you and I'm willing to waste my time sitting here like a clueless d*ckhead while you're late!"). The text says, "text when YOU arrive" Why? Two reasons. 1. Because I'm not there lmao, and... 2. Girls are always late. lmao. I'd guess only 10% of my dates have ever been "on time." If she ghosts this text, then she just straight up flaked on you. That's all the confirmation you need. Congrats, you just won yourself a free evening. LOL. But usually... Assuming she's acting in good faith... At this point, she'll fess up: "OK, running 15 minutes late but omw." Eventually, when she arrives she'll text you, "ok i'm here!" Obviously, when she arrives, you are nowhere to be found. She's usually waiting by the front entrance. After a minute or two you text something like, "ok omw" That way... You know she's there -- without having to sit in the venue and wait while she inevitably shows up 20-30 minutes late. And voila'. There you have it. A texting sequence I've used a million times. A texting sequence, that I'm sure would've helped this guy. P.S. Unrelated, but... After getting flaked on, he texts the girl: "we agree to a time and place to meet and you haven't made an effort...I don't appreciate having my time wasted." Then proceeds to explain how the person in the lower frame is always explaining themselves to the person with the higher frame. And yet, here he is. Explaining himself to her: "I don't appreciate having my time wasted." Because he's in the lower frame. lol. Good rule of thumb: If you ever have to verbalize your boundaries to a woman... You're not being "alpha" or "masculine." Your frame, is in fact, f*cked lmao.

"How to Confirm A Date -- The Day of the Date." I'm not sure what happened to this guy leading up to the date. I don't have the text exchange. But even when he texts her, "I'm on my way to the date" -- that's a little bit of a red flag on this guy's "method." All of which begs the question: How do you confirm a date...the day of the date? Plenty of ways to skin this cat. Here's one: Assuming the time and place are already set... On the afternoon of the date (somewhere between noon and 1 p.m.) Send a soft confirmation text. Do not send: "Hey are we still on for tonight at 7:30 p.m. ? (Needy and clueless). It's hot as fck on the east coast right now. So I'd probably send something like... "Feel like these ice cold margs are gonna hit tonight" I'm painting a picture. It sounds fun and relaxing because hey, who doesn't love drinking a margarita on a hot summer evening. And it subtly cues that it's her turn to confirm. Her: "omg yeh its crazy hot looking fwd to it :)" If she says nothing then you know a flake is likely in the cards. So what do you do? Either way, you do the same thing. Here's what I mean: I always pick a bar walking distance from my place -- so ymmv. But 15 minutes before the date... You text something like, "text when you arrive" It's a vague text but the way it's worded is crucial: If you read closely, it does NOT say nor imply: "I've arrived. So let me know when you've arrived." (Translation: "I'm super eager to meet you and I'm willing to waste my time sitting here like a clueless dckhead while you're late!"). The text says, "text when YOU arrive" Why? Two reasons. 1. Because I'm not there lmao, and... 2. Girls are always late. lmao. I'd guess only 10% of my dates have ever been "on time." If she ghosts this text, then she just straight up flaked on you. That's all the confirmation you need. Congrats, you just won yourself a free evening. LOL. But usually... Assuming she's acting in good faith... At this point, she'll fess up: "OK, running 15 minutes late but omw." Eventually, when she arrives she'll text you, "ok i'm here!" Obviously, when she arrives, you are nowhere to be found. She's usually waiting by the front entrance. After a minute or two you text something like, "ok omw" That way... You know she's there -- without having to sit in the venue and wait while she inevitably shows up 20-30 minutes late. And voila'. There you have it. A texting sequence I've used a million times. A texting sequence, that I'm sure would've helped this guy. P.S. Unrelated, but... After getting flaked on, he texts the girl: "we agree to a time and place to meet and you haven't made an effort...I don't appreciate having my time wasted." Then proceeds to explain how the person in the lower frame is always explaining themselves to the person with the higher frame. And yet, here he is. Explaining himself to her: "I don't appreciate having my time wasted." Because he's in the lower frame. lol. Good rule of thumb: If you ever have to verbalize your boundaries to a woman... You're not being "alpha" or "masculine." Your frame, is in fact, fcked lmao.

The Rizz Report

40,591 次观看 • 29 天前

🎙️ Episode 10 of [trading places] featuring Rick Baker from Blackbird Ventures is out now. This week on trading places, hosts Dave McClure and Aman Verjee cover the latest tech news, including OpenAI's path to a trillion-dollar IPO, Big Tech's massive AI spending spree, and Tether's $500 billion valuation. Plus, we sit down with Rick Baker, Managing Partner at Blackbird Venture Capital, to discuss the incredible Canva story, secondary transactions, and building Australia's venture ecosystem from the ground up. 📰 THIS WEEK'S NEWS 🤖 OpenAI's IPO Plans -Potential $1 trillion IPO target -Microsoft ownership restructure (49% → 27%) -California AG blesses for-profit transition -Sam Altman hints at revenue north of $100B 💰 Big Tech AI Spending -Microsoft, Amazon, Alphabet, Meta spending $125B/quarter on AI infrastructure -Meta raises $30B in corporate bonds -Oracle raises $38B for data center expansion -Power constraints emerging as key bottleneck 📈 Secondary Market Consolidation -Morgan Stanley acquires EquityZen -Goldman Sachs acquired Industry Ventures -Signals expansion of secondary market opportunities 🚀 IPO & Funding News -Navan's challenging IPO (down 20% on day one) -Mer raises $350M Series C at $10B valuation (5x step-up) -Securitize going public via SPAC at $1.2B valuation 🪙 Stablecoin Market - considering $500B valuation round -Coinbase 🛡️ reportedly pursuing $2B acquisition of BVNK -Stablecoin revenue growing 300M+ per quarter 🎙️ FEATURED GUEST: RICK BAKER, MANAGING PARTNER @ BLACKBIRD VENTURES The Canva Story -Rick shares the incredible journey of Blackbird's investment in Canva—from a $250K seed investment to a company now valued at $40B. -GP-Led Secondary Transactions -Rick walks through Blackbird's 2019 secondary sale: -Sold ~$120M (1/3 of Fund I) at 93% of NAV -Returned 3.5x to LPs while maintaining 9.5x exposure -Used Lazard to run a competitive process -StepStone + Australian super fund won the bid Managing Concentration Risk -Owned 15% of Canva at peak, now ~11% -Balance between maximizing returns and managing risk -LP perspectives range from "sell everything" to "hold forever" -Strategic sales during primary rounds to unlock growth capital Australian VC Ecosystem -Superannuation system: 12% of salary mandated into pension funds -$4T AUD pool of long-term capital -Reset after GFC: Blackbird, Square Peg, Airtree, Main Sequence -Circle of life: Atlassian/Canva alumni starting next wave 💎 VALUATION CORNER: TETHER @ $500 BILLION -Deep Dive on Tether -Aman analyzes whether the world's largest stablecoin issuer is worth a $500B valuation: -$13B+ in annual profit (2x BlackRock's profitability) -75% market share vs. Circle's 20% -36x P/E ratio vs. Circle at 240x -Medium transparency, aggressive reserve policy -Regulatory uncertainty in U.S. market 0:00 - Intro 01:12 -[ tech & vc news ] 01:21 - OpenAI Restructuring | $1T IPO? 08:24 - Big Tech Hyperscalers' Earnings and $125 Billion in Quarterly AI Spending 10:47 - Why This AI Boom is Different 15:58 - Morgan Stanley Acquires EquityZen 17:39 - Navan's Public Offering Performance 21:05 - Mercor Raises at a $10 Billion Valuation 22:23 - Securitize Going Public via SPAC ($1.25B) 24:37 - Tether's $500B Valuation Rumor 28:05 - [ interview: blackbird vc / rick baker ] 28:49 - Rick Baker's Background and Founding the MLC Venture Program 35:56 - The Canva Story 45:06 - The Australian Venture Capital Market 01:07:44 - How the Secondary Market Solves the Liquidity Problem 01:15:48 - [ valuation corner: tether] 01:13:30 - Tether's Aggressive vs. $CIRC’s Conservative Reserve Policy 01:16:32 - Calculating Tether's Valuation Based on P/E 01:24:00 - The Regulatory Uncertainty for Stablecoins 01:31:30 - Final Thoughts on Tether's $500B Valuation & Stablecoin Market DISCLAIMER: This podcast is for informational and entertainment purposes only. Nothing discussed should be construed as investment advice. Always conduct your own research and consult with qualified professionals before making investment decisions.

🎙️ Episode 10 of [trading places] featuring Rick Baker from Blackbird Ventures is out now. This week on trading places, hosts Dave McClure and Aman Verjee cover the latest tech news, including OpenAI's path to a trillion-dollar IPO, Big Tech's massive AI spending spree, and Tether's $500 billion valuation. Plus, we sit down with Rick Baker, Managing Partner at Blackbird Venture Capital, to discuss the incredible Canva story, secondary transactions, and building Australia's venture ecosystem from the ground up. 📰 THIS WEEK'S NEWS 🤖 OpenAI's IPO Plans -Potential $1 trillion IPO target -Microsoft ownership restructure (49% → 27%) -California AG blesses for-profit transition -Sam Altman hints at revenue north of $100B 💰 Big Tech AI Spending -Microsoft, Amazon, Alphabet, Meta spending $125B/quarter on AI infrastructure -Meta raises $30B in corporate bonds -Oracle raises $38B for data center expansion -Power constraints emerging as key bottleneck 📈 Secondary Market Consolidation -Morgan Stanley acquires EquityZen -Goldman Sachs acquired Industry Ventures -Signals expansion of secondary market opportunities 🚀 IPO & Funding News -Navan's challenging IPO (down 20% on day one) -Mer raises $350M Series C at $10B valuation (5x step-up) -Securitize going public via SPAC at $1.2B valuation 🪙 Stablecoin Market - considering $500B valuation round -Coinbase 🛡️ reportedly pursuing $2B acquisition of BVNK -Stablecoin revenue growing 300M+ per quarter 🎙️ FEATURED GUEST: RICK BAKER, MANAGING PARTNER @ BLACKBIRD VENTURES The Canva Story -Rick shares the incredible journey of Blackbird's investment in Canva—from a $250K seed investment to a company now valued at $40B. -GP-Led Secondary Transactions -Rick walks through Blackbird's 2019 secondary sale: -Sold ~$120M (1/3 of Fund I) at 93% of NAV -Returned 3.5x to LPs while maintaining 9.5x exposure -Used Lazard to run a competitive process -StepStone + Australian super fund won the bid Managing Concentration Risk -Owned 15% of Canva at peak, now ~11% -Balance between maximizing returns and managing risk -LP perspectives range from "sell everything" to "hold forever" -Strategic sales during primary rounds to unlock growth capital Australian VC Ecosystem -Superannuation system: 12% of salary mandated into pension funds -$4T AUD pool of long-term capital -Reset after GFC: Blackbird, Square Peg, Airtree, Main Sequence -Circle of life: Atlassian/Canva alumni starting next wave 💎 VALUATION CORNER: TETHER @ $500 BILLION -Deep Dive on Tether -Aman analyzes whether the world's largest stablecoin issuer is worth a $500B valuation: -$13B+ in annual profit (2x BlackRock's profitability) -75% market share vs. Circle's 20% -36x P/E ratio vs. Circle at 240x -Medium transparency, aggressive reserve policy -Regulatory uncertainty in U.S. market 0:00 - Intro 01:12 -[ tech & vc news ] 01:21 - OpenAI Restructuring | $1T IPO? 08:24 - Big Tech Hyperscalers' Earnings and $125 Billion in Quarterly AI Spending 10:47 - Why This AI Boom is Different 15:58 - Morgan Stanley Acquires EquityZen 17:39 - Navan's Public Offering Performance 21:05 - Mercor Raises at a $10 Billion Valuation 22:23 - Securitize Going Public via SPAC ($1.25B) 24:37 - Tether's $500B Valuation Rumor 28:05 - [ interview: blackbird vc / rick baker ] 28:49 - Rick Baker's Background and Founding the MLC Venture Program 35:56 - The Canva Story 45:06 - The Australian Venture Capital Market 01:07:44 - How the Secondary Market Solves the Liquidity Problem 01:15:48 - [ valuation corner: tether] 01:13:30 - Tether's Aggressive vs. $CIRC’s Conservative Reserve Policy 01:16:32 - Calculating Tether's Valuation Based on P/E 01:24:00 - The Regulatory Uncertainty for Stablecoins 01:31:30 - Final Thoughts on Tether's $500B Valuation & Stablecoin Market DISCLAIMER: This podcast is for informational and entertainment purposes only. Nothing discussed should be construed as investment advice. Always conduct your own research and consult with qualified professionals before making investment decisions.

trading places

11,519 次观看 • 10 个月前

PhD Students – How to convert your rough notes into a paper draft in 1 hour? Let’s first quickly understand the concept of rough notes. As a PhD student, you often read papers and make notes. Sometimes, you extract data from the papers you read. You record this data in an excel sheet. Irrespective of how you record your notes or data, you can convert it into a paper draft. More interesting, you can do this automatically. 𝐖𝐡𝐲 𝐭𝐨 𝐜𝐨𝐧𝐯𝐞𝐫𝐭 𝐲𝐨𝐮𝐫 𝐧𝐨𝐭𝐞𝐬 𝐢𝐧𝐭𝐨 𝐚 𝐩𝐚𝐩𝐞𝐫 𝐝𝐫𝐚𝐟𝐭? ➟ Difficult to comprehend your notes/data ➟ The notes are scattered in different places ➟ Need to synthesize a broader idea from your notes ➟ Need to write paper based on data noted 𝐇𝐨𝐰 𝐭𝐨 𝐜𝐨𝐧𝐯𝐞𝐫𝐭 𝐲𝐨𝐮𝐫 𝐧𝐨𝐭𝐞𝐬 𝐢𝐧𝐭𝐨 𝐚 𝐩𝐚𝐩𝐞𝐫 𝐝𝐫𝐚𝐟𝐭? 1. Go to and log in. 2. Open a blank document to start. 3. Click on 𝑊𝑟𝑖𝑡𝑒 on the right menu. 4. Click on 𝑢𝑝𝑙𝑜𝑎𝑑/𝑎𝑡𝑡𝑎𝑐ℎ button to upload your rough notes. 5. Use either pre-defined prompts or write your own. 6. For example, use the prompt – 𝐷𝑟𝑎𝑓𝑡 𝑎 𝑙𝑖𝑡𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑟𝑒𝑣𝑖𝑒𝑤. 7. Paperpal will convert your notes a first draft of literature review. 8. Unlike ChatGPT, it will include real references your notes have. 9. You can give follow up instruction to modify the output. 10. For example, you can instruct – 𝑚𝑎𝑘𝑒 𝑜𝑢𝑡𝑝𝑢𝑡 𝑚𝑜𝑟𝑒 𝑐𝑜𝑛𝑐𝑖𝑠𝑒. 11. Paperpal will provide a concise alternative. 12. You can continue writing using the following options. ➝ Keep Writing ➝ Expand on ➝ Write a counter argument ➝ Write a transition sentence ➝ Write an impact statement 13. You can either accept or discard the generated text. Following this process will generate a paper draft for you. However, it is important to note that it is only a draft. You need to put your own human insight into it to polish it. You also need to carefully cross check the outputs. Please note this tutorial and tool is to facilitate you. It does not intend or even can replace you as a researcher. Try the Write 2.0 feature of Paperpal. Here is the link: Use code – FAHPP30 to get 30% off on Paperpal Prime. Anything you'd like to add?

PhD Students – How to convert your rough notes into a paper draft in 1 hour? Let’s first quickly understand the concept of rough notes. As a PhD student, you often read papers and make notes. Sometimes, you extract data from the papers you read. You record this data in an excel sheet. Irrespective of how you record your notes or data, you can convert it into a paper draft. More interesting, you can do this automatically. 𝐖𝐡𝐲 𝐭𝐨 𝐜𝐨𝐧𝐯𝐞𝐫𝐭 𝐲𝐨𝐮𝐫 𝐧𝐨𝐭𝐞𝐬 𝐢𝐧𝐭𝐨 𝐚 𝐩𝐚𝐩𝐞𝐫 𝐝𝐫𝐚𝐟𝐭? ➟ Difficult to comprehend your notes/data ➟ The notes are scattered in different places ➟ Need to synthesize a broader idea from your notes ➟ Need to write paper based on data noted 𝐇𝐨𝐰 𝐭𝐨 𝐜𝐨𝐧𝐯𝐞𝐫𝐭 𝐲𝐨𝐮𝐫 𝐧𝐨𝐭𝐞𝐬 𝐢𝐧𝐭𝐨 𝐚 𝐩𝐚𝐩𝐞𝐫 𝐝𝐫𝐚𝐟𝐭? 1. Go to and log in. 2. Open a blank document to start. 3. Click on 𝑊𝑟𝑖𝑡𝑒 on the right menu. 4. Click on 𝑢𝑝𝑙𝑜𝑎𝑑/𝑎𝑡𝑡𝑎𝑐ℎ button to upload your rough notes. 5. Use either pre-defined prompts or write your own. 6. For example, use the prompt – 𝐷𝑟𝑎𝑓𝑡 𝑎 𝑙𝑖𝑡𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑟𝑒𝑣𝑖𝑒𝑤. 7. Paperpal will convert your notes a first draft of literature review. 8. Unlike ChatGPT, it will include real references your notes have. 9. You can give follow up instruction to modify the output. 10. For example, you can instruct – 𝑚𝑎𝑘𝑒 𝑜𝑢𝑡𝑝𝑢𝑡 𝑚𝑜𝑟𝑒 𝑐𝑜𝑛𝑐𝑖𝑠𝑒. 11. Paperpal will provide a concise alternative. 12. You can continue writing using the following options. ➝ Keep Writing ➝ Expand on ➝ Write a counter argument ➝ Write a transition sentence ➝ Write an impact statement 13. You can either accept or discard the generated text. Following this process will generate a paper draft for you. However, it is important to note that it is only a draft. You need to put your own human insight into it to polish it. You also need to carefully cross check the outputs. Please note this tutorial and tool is to facilitate you. It does not intend or even can replace you as a researcher. Try the Write 2.0 feature of Paperpal. Here is the link: Use code – FAHPP30 to get 30% off on Paperpal Prime. Anything you'd like to add?

Faheem Ullah

34,237 次观看 • 1 年前

Attendance was down AND I didn't get the coveted Charles Hoskinson selfie at this year's @NFTxLV. But here's why it doesn't bother me one bit: The only thing better than a conversation with Charles is a conversation with friends. I met some of you for the first time, like @j_moyns, Demosthenes, Squashua 🍩, VivaLaCoin, @cashpognft, and Goofycrisp, to only name a few. I wouldn't still be here if it wasn't for the Cardano community. Seeing web3innovationnerds and Charles show up for the NFT space was another highlight. Not only did they attend, but they also showed up financially as sponsors. They wanted this event to happen just as much as we did. Say what you will about what can be improved, but this is what supporting the community looks like. I loved the vibe. It was professional and organized without feeling sterile and serious. It reminded me more of a great community farmers market. Lower attendance meant that founders could have more meaningful conversations. It was less overwhelming and felt more personal. This is what makes Cardano unique in the first place and something we should lean into. NFTxLV doesn't have to be a smaller version of every other crypto conference. I had great conversations with 25 projects in 1 day, from well-established ones like cornucopias and CHERI BOTHA to exciting newcomers like @rflxt, Grabb.it, and WayUp. Massive thanks to everyone who took the time to chat. Was the conference perfect? No. Can we do a better job of bringing people in from outside the Cardano bubble? Yes. More on that in a video later this week. But just like last year, I left Vegas feeling re-energized and excited about our space. It reminded me that what we do creates real value for real people. See you in 2024. (Shoutout to HOLD for that banger of a song)

Attendance was down AND I didn't get the coveted Charles Hoskinson selfie at this year's @NFTxLV. But here's why it doesn't bother me one bit: The only thing better than a conversation with Charles is a conversation with friends. I met some of you for the first time, like @j_moyns, Demosthenes, Squashua 🍩, VivaLaCoin, @cashpognft, and Goofycrisp, to only name a few. I wouldn't still be here if it wasn't for the Cardano community. Seeing web3innovationnerds and Charles show up for the NFT space was another highlight. Not only did they attend, but they also showed up financially as sponsors. They wanted this event to happen just as much as we did. Say what you will about what can be improved, but this is what supporting the community looks like. I loved the vibe. It was professional and organized without feeling sterile and serious. It reminded me more of a great community farmers market. Lower attendance meant that founders could have more meaningful conversations. It was less overwhelming and felt more personal. This is what makes Cardano unique in the first place and something we should lean into. NFTxLV doesn't have to be a smaller version of every other crypto conference. I had great conversations with 25 projects in 1 day, from well-established ones like cornucopias and CHERI BOTHA to exciting newcomers like @rflxt, Grabb.it, and WayUp. Massive thanks to everyone who took the time to chat. Was the conference perfect? No. Can we do a better job of bringing people in from outside the Cardano bubble? Yes. More on that in a video later this week. But just like last year, I left Vegas feeling re-energized and excited about our space. It reminded me that what we do creates real value for real people. See you in 2024. (Shoutout to HOLD for that banger of a song)

CardanoThor

72,744 次观看 • 2 年前

Let’s install the Verified Identity Skill on our agent 𝘁𝗼 𝗯𝗲 𝗲𝗹𝗶𝗴𝗶𝗯𝗹𝗲 𝗳𝗼𝗿 𝘂𝗽𝗰𝗼𝗺𝗶𝗻𝗴 𝗙𝗔𝗜𝗔𝗥 𝗿𝗲𝘄𝗮𝗿𝗱𝘀 from Billions Network (Commands to install it are here with video tutorial) Remember, if you don’t do this and have only verified your agent, you 𝐰𝐨𝐧’𝐭 be eligible for FAIAR rewards Before this, as I made a post an hour ago, I’m assuming you all have: - verified your agent on Billions using Termux - not uninstalled or cleared data of that Termux - and if you uninstalled it earlier, you’ve verified a new agent and are ready to install the skill Let’s move ahead with the commands Command 1 - npx clawhub@latest install verified-agent-identity It will ask for your permission to install the latest clawhub version. Type "Y" and press enter Command 2 - once the previous download completes, run this command npx skills add BillionsNetwork/verified-agent-identity Type "Y" and enter again. I’ve attached a video tutorial for the remaining steps, as it’s difficult to explain in text That’s it, congratulations, you have successfully installed the Verified Identity Skill on your agent gBillions 💙

Let’s install the Verified Identity Skill on our agent 𝘁𝗼 𝗯𝗲 𝗲𝗹𝗶𝗴𝗶𝗯𝗹𝗲 𝗳𝗼𝗿 𝘂𝗽𝗰𝗼𝗺𝗶𝗻𝗴 𝗙𝗔𝗜𝗔𝗥 𝗿𝗲𝘄𝗮𝗿𝗱𝘀 from Billions Network (Commands to install it are here with video tutorial) Remember, if you don’t do this and have only verified your agent, you 𝐰𝐨𝐧’𝐭 be eligible for FAIAR rewards Before this, as I made a post an hour ago, I’m assuming you all have: - verified your agent on Billions using Termux - not uninstalled or cleared data of that Termux - and if you uninstalled it earlier, you’ve verified a new agent and are ready to install the skill Let’s move ahead with the commands Command 1 - npx clawhub@latest install verified-agent-identity It will ask for your permission to install the latest clawhub version. Type "Y" and press enter Command 2 - once the previous download completes, run this command npx skills add BillionsNetwork/verified-agent-identity Type "Y" and enter again. I’ve attached a video tutorial for the remaining steps, as it’s difficult to explain in text That’s it, congratulations, you have successfully installed the Verified Identity Skill on your agent gBillions 💙

Sam

170,106 次观看 • 4 个月前

In many cases, the best AI companies aren't replacing software. They're giving it a login. Every software company for years has made the same pitch to manufacturers: clean APIs, migrate your stack, rip out your ERP It rarely works well. The ERP is the company brain. Years of data. You can't rip it out any more than you can rip out someone's memory nikolas & Co-Founder lukas figured out the obvious thing that everyone missed Stop trying to replace the software. Give an AI employee a login instead. Walter signs into SAP, Microsoft Dynamics 365, and Oracle the way a new hire would Ready to go from day 1. Works out of Teams and email like the rest of the team. Reads orders. Enters them. Places supplier POs. Catches pricing errors before they ship... Not another dashboard. Not another integration project. Not another rip and replace. A purchase order that used to take 15 minutes now takes a few seconds. The insight came from a $ 100M+ manufacturer who had a full-time employee doing nothing but typing purchase orders into an ERP Not because the work was valuable. Because the software demanded it. With Walter, your software stays. The manual work disappears. 🎙️ nikolas, CEO & Co-Founder of Walter on Fondo.com START Huge thanks to Corgi for making this episode possible!

In many cases, the best AI companies aren't replacing software. They're giving it a login. Every software company for years has made the same pitch to manufacturers: clean APIs, migrate your stack, rip out your ERP It rarely works well. The ERP is the company brain. Years of data. You can't rip it out any more than you can rip out someone's memory nikolas & Co-Founder lukas figured out the obvious thing that everyone missed Stop trying to replace the software. Give an AI employee a login instead. Walter signs into SAP, Microsoft Dynamics 365, and Oracle the way a new hire would Ready to go from day 1. Works out of Teams and email like the rest of the team. Reads orders. Enters them. Places supplier POs. Catches pricing errors before they ship... Not another dashboard. Not another integration project. Not another rip and replace. A purchase order that used to take 15 minutes now takes a few seconds. The insight came from a $ 100M+ manufacturer who had a full-time employee doing nothing but typing purchase orders into an ERP Not because the work was valuable. Because the software demanded it. With Walter, your software stays. The manual work disappears. 🎙️ nikolas, CEO & Co-Founder of Walter on Fondo.com START Huge thanks to Corgi for making this episode possible!

David J Phillips

58,965 次观看 • 2 个月前