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Meta open-sourced a brain-to-text system that reaches 78% word accuracy without surgery. Brain2Qwerty v2 converts non-invasive brain recordings into text with 61% average word accuracy and 78% for its strongest participant. The system reads MEG signals from a helmet, not electrodes placed inside brain tissue. 9 volunteers typed about...

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Rohan Paul

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17,127 görüntüleme • 1 ay önce •via X (Twitter)

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There’s no other way to describe it: Your child’s physical and intellectual growth between 12 and 24 months is exponential. At one year of age many children are speaking their first words and taking their first unsteady steps. A year later and you’ll hardly recognize them as the same child. Check out this little one (shown here approaching two) who manages to string together, not a word or two, but a six word sentence (requesting to be taken to her grandmother’s house). When her father asks her to repeat herself, she lays it on thick, adding a pair of extra pleases at the start of the sentence for good measure - extending her request to 8 words. Isn’t it amazing to think that less than 12 months earlier this little one likely spoke her first word? Such amazing growth in her vocabulary and sophistication. Kudos little one! Here’s hoping you made it over to grandma’s house. When did your baby speak their first words? Their first full sentences? This adorable language learner was shared to TT by rosemeblue_alllove.
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There’s no other way to describe it: Your child’s physical and intellectual growth between 12 and 24 months is exponential. At one year of age many children are speaking their first words and taking their first unsteady steps. A year later and you’ll hardly recognize them as the same child. Check out this little one (shown here approaching two) who manages to string together, not a word or two, but a six word sentence (requesting to be taken to her grandmother’s house). When her father asks her to repeat herself, she lays it on thick, adding a pair of extra pleases at the start of the sentence for good measure - extending her request to 8 words. Isn’t it amazing to think that less than 12 months earlier this little one likely spoke her first word? Such amazing growth in her vocabulary and sophistication. Kudos little one! Here’s hoping you made it over to grandma’s house. When did your baby speak their first words? Their first full sentences? This adorable language learner was shared to TT by rosemeblue_alllove.

Dan Wuori

232,738 görüntüleme • 2 yıl önce

Vector Database by Hand ✍️ Vector databases are revolutionizing how we search and analyze complex data. They have become the backbone of Retrieval Augmented Generation (#RAG). How do vector databases work? [1] Given ↳ A dataset of three sentences, each has 3 words (or tokens) ↳ In practice, a dataset may contain millions or billions of sentences. The max number of tokens may be tens of thousands (e.g., 32,768 mistral-7b). Process "how are you" [2] 🟨 Word Embeddings ↳ For each word, look up corresponding word embedding vector from a table of 22 vectors, where 22 is the vocabulary size. ↳ In practice, the vocabulary size can be tens of thousands. The word embedding dimensions are in the thousands (e.g., 1024, 4096) [3] 🟩 Encoding ↳ Feed the sequence of word embeddings to an encoder to obtain a sequence of feature vectors, one per word. ↳ Here, the encoder is a simple one layer perceptron (linear layer + ReLU) ↳ In practice, the encoder is a transformer or one of its many variants. [4] 🟩 Mean Pooling ↳ Merge the sequence of feature vectors into a single vector using "mean pooling" which is to average across the columns. ↳ The result is a single vector. We often call it "text embeddings" or "sentence embeddings." ↳ Other pooling techniques are possible, such as CLS. But mean pooling is the most common. [5] 🟦 Indexing ↳ Reduce the dimensions of the text embedding vector by a projection matrix. The reduction rate is 50% (4->2). ↳ In practice, the values in this projection matrix is much more random. ↳ The purpose is similar to that of hashing, which is to obtain a short representation to allow faster comparison and retrieval. ↳ The resulting dimension-reduced index vector is saved in the vector storage. [6] Process "who are you" ↳ Repeat [2]-[5] [7] Process "who am I" ↳ Repeat [2]-[5] Now we have indexed our dataset in the vector database. [8] 🟥 Query: "am I you" ↳ Repeat [2]-[5] ↳ The result is a 2-d query vector. [9] 🟥 Dot Products ↳ Take dot product between the query vector and database vectors. They are all 2-d. ↳ The purpose is to use dot product to estimate similarity. ↳ By transposing the query vector, this step becomes a matrix multiplication. [10] 🟥 Nearest Neighbor ↳ Find the largest dot product by linear scan. ↳ The sentence with the highest dot product is "who am I" ↳ In practice, because scanning billions of vectors is slow, we use an Approximate Nearest Neighbor (ANN) algorithm like the Hierarchical Navigable Small Worlds (HNSW).
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Vector Database by Hand ✍️ Vector databases are revolutionizing how we search and analyze complex data. They have become the backbone of Retrieval Augmented Generation (#RAG). How do vector databases work? [1] Given ↳ A dataset of three sentences, each has 3 words (or tokens) ↳ In practice, a dataset may contain millions or billions of sentences. The max number of tokens may be tens of thousands (e.g., 32,768 mistral-7b). Process "how are you" [2] 🟨 Word Embeddings ↳ For each word, look up corresponding word embedding vector from a table of 22 vectors, where 22 is the vocabulary size. ↳ In practice, the vocabulary size can be tens of thousands. The word embedding dimensions are in the thousands (e.g., 1024, 4096) [3] 🟩 Encoding ↳ Feed the sequence of word embeddings to an encoder to obtain a sequence of feature vectors, one per word. ↳ Here, the encoder is a simple one layer perceptron (linear layer + ReLU) ↳ In practice, the encoder is a transformer or one of its many variants. [4] 🟩 Mean Pooling ↳ Merge the sequence of feature vectors into a single vector using "mean pooling" which is to average across the columns. ↳ The result is a single vector. We often call it "text embeddings" or "sentence embeddings." ↳ Other pooling techniques are possible, such as CLS. But mean pooling is the most common. [5] 🟦 Indexing ↳ Reduce the dimensions of the text embedding vector by a projection matrix. The reduction rate is 50% (4->2). ↳ In practice, the values in this projection matrix is much more random. ↳ The purpose is similar to that of hashing, which is to obtain a short representation to allow faster comparison and retrieval. ↳ The resulting dimension-reduced index vector is saved in the vector storage. [6] Process "who are you" ↳ Repeat [2]-[5] [7] Process "who am I" ↳ Repeat [2]-[5] Now we have indexed our dataset in the vector database. [8] 🟥 Query: "am I you" ↳ Repeat [2]-[5] ↳ The result is a 2-d query vector. [9] 🟥 Dot Products ↳ Take dot product between the query vector and database vectors. They are all 2-d. ↳ The purpose is to use dot product to estimate similarity. ↳ By transposing the query vector, this step becomes a matrix multiplication. [10] 🟥 Nearest Neighbor ↳ Find the largest dot product by linear scan. ↳ The sentence with the highest dot product is "who am I" ↳ In practice, because scanning billions of vectors is slow, we use an Approximate Nearest Neighbor (ANN) algorithm like the Hierarchical Navigable Small Worlds (HNSW).

Tom Yeh

192,022 görüntüleme • 2 yıl önce

🇷🇺 Russia’s Starlink killers showcase new era of electronic battlefield warfare Russia has ramped-up EW use to detect and jam Elon Musk’s Starlink terminals and satellites, Ukrainian media reports. 👉 Meet Russia’s key counter-Starlink systems: 🔸 Volna Kupol Garant Russia’s latest electronic warfare system reportedly uses a directed high-frequency radio beam to disrupt Starlink operations. Rather than damaging satellites orbiting roughly 500 kilometers above Earth, the system blinds them – cutting their ability to connect with ground terminals while they remain under attack. According to reports, Volna is a mobile system built around six trailers. Each carries a pair of steerable satellite dishes mounted on rotating platforms. A single battery is reportedly capable of denying Starlink coverage across an area of up to 20 sq km. Some analysts say the system was previously referenced under the designation Peresvet-M, although this has not been independently confirmed. Ukrainian sources claim Volna was first deployed during Russia's offensive in the Kharkov region in 2024. They also say its use has increased significantly in recent months. 🔸 Tobol The secretive Russian EW complex is reportedly used to disrupt signals from NATO-linked satellite networks, including GPS, Galileo, and Starlink. Reports claim that Tobol attacks satellite communications on both ends of the link – jamming downlinks from satellites to ground receivers and uplinks from Earth to orbit. Its power and range also allegedly allow it to create an electromagnetic "umbrella." 🔸 Kalinka The system is designed to hunt down satellite communications signals, including those transmitted by Starlink terminals at distances of up to 15 km. It can reportedly track and lock onto even Starshield – SpaceX’s hardened military variant of Starlink. Western media warns that while Tobol disrupts GPS signals on a broad scale, the Kalinka’s precision-targeting capabilities could pose a more direct threat to specific military operations. 🔸 Krasukha The Krasukha-S4 is designed to neutralize reconnaissance satellites, ground-based radar installations, and airborne surveillance systems. It does so by emitting powerful electronic jamming signals that disrupt key radar bands and other radio-frequency emissions. A standard Krasukha-S4 battery consists of two vehicles and has an operational range exceeding 300 kilometers. 🔸 Borshchevik The light mobile system is designed to detect and geolocate Starlink terminals within a 180-degree sector at ranges of up to 10 km, with a reported accuracy of five meters. Using direction-finding and biangulation algorithms, it can locate a target in less than three minutes at a single scanning position. The Borshchevik-2 airborne system hunts Starlink signals from the sky, with reported accuracy down to 0.4 m.
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🇷🇺 Russia’s Starlink killers showcase new era of electronic battlefield warfare Russia has ramped-up EW use to detect and jam Elon Musk’s Starlink terminals and satellites, Ukrainian media reports. 👉 Meet Russia’s key counter-Starlink systems: 🔸 Volna Kupol Garant Russia’s latest electronic warfare system reportedly uses a directed high-frequency radio beam to disrupt Starlink operations. Rather than damaging satellites orbiting roughly 500 kilometers above Earth, the system blinds them – cutting their ability to connect with ground terminals while they remain under attack. According to reports, Volna is a mobile system built around six trailers. Each carries a pair of steerable satellite dishes mounted on rotating platforms. A single battery is reportedly capable of denying Starlink coverage across an area of up to 20 sq km. Some analysts say the system was previously referenced under the designation Peresvet-M, although this has not been independently confirmed. Ukrainian sources claim Volna was first deployed during Russia's offensive in the Kharkov region in 2024. They also say its use has increased significantly in recent months. 🔸 Tobol The secretive Russian EW complex is reportedly used to disrupt signals from NATO-linked satellite networks, including GPS, Galileo, and Starlink. Reports claim that Tobol attacks satellite communications on both ends of the link – jamming downlinks from satellites to ground receivers and uplinks from Earth to orbit. Its power and range also allegedly allow it to create an electromagnetic "umbrella." 🔸 Kalinka The system is designed to hunt down satellite communications signals, including those transmitted by Starlink terminals at distances of up to 15 km. It can reportedly track and lock onto even Starshield – SpaceX’s hardened military variant of Starlink. Western media warns that while Tobol disrupts GPS signals on a broad scale, the Kalinka’s precision-targeting capabilities could pose a more direct threat to specific military operations. 🔸 Krasukha The Krasukha-S4 is designed to neutralize reconnaissance satellites, ground-based radar installations, and airborne surveillance systems. It does so by emitting powerful electronic jamming signals that disrupt key radar bands and other radio-frequency emissions. A standard Krasukha-S4 battery consists of two vehicles and has an operational range exceeding 300 kilometers. 🔸 Borshchevik The light mobile system is designed to detect and geolocate Starlink terminals within a 180-degree sector at ranges of up to 10 km, with a reported accuracy of five meters. Using direction-finding and biangulation algorithms, it can locate a target in less than three minutes at a single scanning position. The Borshchevik-2 airborne system hunts Starlink signals from the sky, with reported accuracy down to 0.4 m.

Sputnik

25,422 görüntüleme • 17 gün önce

🇨🇳 Another great Chinese Model, OmniHuman-1.5 from ByteDance Turns 1 image plus a voice track into expressive avatar video by pairing a System 1 and System 2 inspired planner with a Diffusion Transformer, Produces coherent motion for over 1 minute with moving camera and multi character scenes. Most avatar models move to the beat of the audio but miss meaning, so gestures feel generic and emotions feel shallow. The fix here is a Multimodal LLM planner that listens to the speech and drafts a structured plan describing intent, emotions, beats, and high level actions, which gives the motion engine clear semantic targets instead of only rhythm. The motion engine is a Multimodal Diffusion Transformer that fuses the plan with audio, the single reference image, and optional text prompts, then synthesizes continuous body, face, and head motion that matches both words and tone. A key trick is a Pseudo Last Frame, a synthetic target that summarizes the next expected state, which stabilizes fusion across modalities and keeps motion consistent over long spans. From just 1 image and speech, the system outputs speaking avatars with synchronized lips, context aware gestures, and continuous camera movement, and it also supports multi character interactions without manual choreography. Reported results show strong lip sync accuracy, high video quality, natural motion, and close match to text prompts, and the same setup works on nonhuman characters too.
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🇨🇳 Another great Chinese Model, OmniHuman-1.5 from ByteDance Turns 1 image plus a voice track into expressive avatar video by pairing a System 1 and System 2 inspired planner with a Diffusion Transformer, Produces coherent motion for over 1 minute with moving camera and multi character scenes. Most avatar models move to the beat of the audio but miss meaning, so gestures feel generic and emotions feel shallow. The fix here is a Multimodal LLM planner that listens to the speech and drafts a structured plan describing intent, emotions, beats, and high level actions, which gives the motion engine clear semantic targets instead of only rhythm. The motion engine is a Multimodal Diffusion Transformer that fuses the plan with audio, the single reference image, and optional text prompts, then synthesizes continuous body, face, and head motion that matches both words and tone. A key trick is a Pseudo Last Frame, a synthetic target that summarizes the next expected state, which stabilizes fusion across modalities and keeps motion consistent over long spans. From just 1 image and speech, the system outputs speaking avatars with synchronized lips, context aware gestures, and continuous camera movement, and it also supports multi character interactions without manual choreography. Reported results show strong lip sync accuracy, high video quality, natural motion, and close match to text prompts, and the same setup works on nonhuman characters too.

Rohan Paul

63,859 görüntüleme • 11 ay önce

Karpathy method + Claude Code reading your whole Obsidian vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.
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Karpathy method + Claude Code reading your whole Obsidian vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.

West Lord

590,875 görüntüleme • 1 ay önce

we sped up distributed inference by up to 5x with decentralized speculative decoding. many don't realize that AI models normally generate text one single word at a time, waiting for the network after every word. speculative decoding changes this by using a "guess & confirm" system, similar to autocomplete. how it's done: 1. draft locally (the guess) instead of waiting for the network, a tiny, fast model on your device guesses the next few words instantly, without waiting for the network. 2. confirm remotely (the check) the massive remote model doesn't generate from scratch; it just checks the draft. it looks at the guesses in a batch and says "yes, yes, no." you get multiple words in the time it usually takes to get one. 3. adaptive logic dsd is smart. if the topic is creative, it lets the draft flow loose. if the topic is math or code, it checks more strictly. it balances speed and precision automatically so your inference almost feel instant. find out more: paper: blog:
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we sped up distributed inference by up to 5x with decentralized speculative decoding. many don't realize that AI models normally generate text one single word at a time, waiting for the network after every word. speculative decoding changes this by using a "guess & confirm" system, similar to autocomplete. how it's done: 1. draft locally (the guess) instead of waiting for the network, a tiny, fast model on your device guesses the next few words instantly, without waiting for the network. 2. confirm remotely (the check) the massive remote model doesn't generate from scratch; it just checks the draft. it looks at the guesses in a batch and says "yes, yes, no." you get multiple words in the time it usually takes to get one. 3. adaptive logic dsd is smart. if the topic is creative, it lets the draft flow loose. if the topic is math or code, it checks more strictly. it balances speed and precision automatically so your inference almost feel instant. find out more: paper: blog:

Parallax

45,584 görüntüleme • 7 ay önce

They say a picture is worth a thousand words. But for your toddler, single words can also convey a whole lot more than you might imagine. Witness this little one who uses the word “whee” (the exhilarated sound she makes going down a playground slide), to carry a whole conversation with her mom. When her mom asks if she’s having a fun day, our hero replies “whee” twice, which here loosely translate to: “Hey, you know that place the park that I love so much? The place I’m always saying whee? Well, I’m kind of disappointed that you haven’t taken me there.” Then she punctuates it with, “I sad.” Pretty amazing, right? As your child’s early language use grows, you can expect to hear a lot of telegraphic speech - one or two word sentences which are typically stripped of grammatical elements. Sentences like “up” (to signify “please pick me up”) or the request “shoe on.” While this telegraphic speech represents a major step forward in language acquisition for children, here’s an important tip: Our most supportive and constructive response as adults may be to treat these early utterances as meaningful… but then extend, rather than repeat them. In other words - rather than replying in kind with “shoe on,” reply with a fully grammatical response. “Oh, yes, if we’re going outside we do need to put your shoes on!” Doing so consistently will provide the types of linguistic models your child needs to continue advancing to more and more sophisticated and grammatical language. Whee! This little playground fan was shared to IG by indyah.
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They say a picture is worth a thousand words. But for your toddler, single words can also convey a whole lot more than you might imagine. Witness this little one who uses the word “whee” (the exhilarated sound she makes going down a playground slide), to carry a whole conversation with her mom. When her mom asks if she’s having a fun day, our hero replies “whee” twice, which here loosely translate to: “Hey, you know that place the park that I love so much? The place I’m always saying whee? Well, I’m kind of disappointed that you haven’t taken me there.” Then she punctuates it with, “I sad.” Pretty amazing, right? As your child’s early language use grows, you can expect to hear a lot of telegraphic speech - one or two word sentences which are typically stripped of grammatical elements. Sentences like “up” (to signify “please pick me up”) or the request “shoe on.” While this telegraphic speech represents a major step forward in language acquisition for children, here’s an important tip: Our most supportive and constructive response as adults may be to treat these early utterances as meaningful… but then extend, rather than repeat them. In other words - rather than replying in kind with “shoe on,” reply with a fully grammatical response. “Oh, yes, if we’re going outside we do need to put your shoes on!” Doing so consistently will provide the types of linguistic models your child needs to continue advancing to more and more sophisticated and grammatical language. Whee! This little playground fan was shared to IG by indyah.

Dan Wuori

77,083 görüntüleme • 1 yıl önce

I've been editing this article about "brain mapping" and connectomics, and I'm just stunned by how quickly the cost estimates to map, say, a mouse brain have plummeted in just the last couple years. It actually seems feasible that we could map the entire human brain -- all 86 billion neurons, and their connections -- in this lifetime. In the 1970s, Sydney Brenner started mapping all the connections between neurons in C. elegans. His team sliced the worm into thin pieces, took photos using an electron microscope, and manually traced and reconstructed each synapse for 302 neurons total. This project took more than a decade of work, and it cost about $16,500 to reconstruct each neuron. Scaling this up to a human brain boggles the mind. Electron microscopy remained the norm in connectomics for decades, because it was the only option available to see synapses at a resolution high enough to be able to trace their paths. Each electron microscope costs several hundreds of thousands of dollars, though, and you need lots of them to map even a mouse brain in a reasonable timeframe. In 2023, the Wellcome Trust released a report estimating how long, and how expensive, it would be to map the mouse connectome (~70M neurons). They estimated that imaging alone would cost $200-300M, and that proofreading (or ensuring that traces between neurons are correct) would cost $7-21 BILLION. (A human can only manually trace about 1 mm of neuron per hour.) Also, the images would occupy about 500 petabytes of data, and getting those data would require 20 electron microscopes running in parallel for about 5 years, continuously. They estimated the whole project would take about 17 years of work. This is, understandably, insane. But now it seems like there's an actual path toward mapping the full mouse brain in about five years for ~$100M dollars. There have been three major breakthroughs in the last year or so: 1/ Expansion microscopy, first developed in 2015, showed that it's possible to "enlarge" the brain by about 5x using a swellable polymer. But an improved method increases this number to >20x expansion, meaning we can now expand brains and image neurons much more easily using cheap light microscopes, rather than expensive electron ones. 2/ E11 Bio (a nonprofit research org) developed protein barcodes that get delivered into brain tissue; each neuron gets a unique combination of barcodes. These cells are then stained with colorful antibodies, which stick to a matching protein barcode, causing each neuron to light up in a distinct color. This makes tracing neurons so much easier. 3/ Google Research released PATHFINDER this May, an AI-based neuron tracing tool that can proofread about 67,200 cubic microns of brain tissue per hour, with very high accuracy. It works on electron micrographs, but something similar could be presumably be developed for the E11 / colorful tag approach. This is an extremely exciting time for neuroscience. (C. elegans connectome below.)
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I've been editing this article about "brain mapping" and connectomics, and I'm just stunned by how quickly the cost estimates to map, say, a mouse brain have plummeted in just the last couple years. It actually seems feasible that we could map the entire human brain -- all 86 billion neurons, and their connections -- in this lifetime. In the 1970s, Sydney Brenner started mapping all the connections between neurons in C. elegans. His team sliced the worm into thin pieces, took photos using an electron microscope, and manually traced and reconstructed each synapse for 302 neurons total. This project took more than a decade of work, and it cost about $16,500 to reconstruct each neuron. Scaling this up to a human brain boggles the mind. Electron microscopy remained the norm in connectomics for decades, because it was the only option available to see synapses at a resolution high enough to be able to trace their paths. Each electron microscope costs several hundreds of thousands of dollars, though, and you need lots of them to map even a mouse brain in a reasonable timeframe. In 2023, the Wellcome Trust released a report estimating how long, and how expensive, it would be to map the mouse connectome (~70M neurons). They estimated that imaging alone would cost $200-300M, and that proofreading (or ensuring that traces between neurons are correct) would cost $7-21 BILLION. (A human can only manually trace about 1 mm of neuron per hour.) Also, the images would occupy about 500 petabytes of data, and getting those data would require 20 electron microscopes running in parallel for about 5 years, continuously. They estimated the whole project would take about 17 years of work. This is, understandably, insane. But now it seems like there's an actual path toward mapping the full mouse brain in about five years for ~$100M dollars. There have been three major breakthroughs in the last year or so: 1/ Expansion microscopy, first developed in 2015, showed that it's possible to "enlarge" the brain by about 5x using a swellable polymer. But an improved method increases this number to >20x expansion, meaning we can now expand brains and image neurons much more easily using cheap light microscopes, rather than expensive electron ones. 2/ E11 Bio (a nonprofit research org) developed protein barcodes that get delivered into brain tissue; each neuron gets a unique combination of barcodes. These cells are then stained with colorful antibodies, which stick to a matching protein barcode, causing each neuron to light up in a distinct color. This makes tracing neurons so much easier. 3/ Google Research released PATHFINDER this May, an AI-based neuron tracing tool that can proofread about 67,200 cubic microns of brain tissue per hour, with very high accuracy. It works on electron micrographs, but something similar could be presumably be developed for the E11 / colorful tag approach. This is an extremely exciting time for neuroscience. (C. elegans connectome below.)

Niko McCarty.

67,020 görüntüleme • 8 ay önce

In 1964, a 17 year old from San Diego conducted the most dangerous psychology experiment ever attempted by a teenager. Randy Gardner stayed awake for 264 hours (11 days) with: • No stimulants • No caffeine • No medical suppressants And Stanford sleep researchers realized too late they couldn't stop him. What happened inside his brain during those 264 hours rewrote everything we thought we knew about consciousness. By day three, Randy's short term memory had completely collapsed. He couldn't remember starting a sentence by the time he reached the end of it. Researchers would ask him to count backward from 100, and he'd stop at 65, staring blankly, having forgotten the entire concept of numbers. But the terrifying part wasn't the memory loss. Randy's brain began creating a second reality that ran parallel to the real one. He'd have full conversations with people who weren't there. He'd walk to locations that didn't exist. His eyes stayed open, his body kept moving, but his mind was living inside elaborate hallucinations that felt completely real to him. Sleep researchers had predicted cognitive decline. They hadn't predicted that the sleep deprived brain would start *manufacturing* an alternate conscious experience to fill the gap. Dr. William Dement, the Stanford researcher monitoring Randy, discovered something that changed sleep science forever. The hallucinations weren't random. They followed the exact same patterns as REM sleep dreams, complete with narrative arcs, emotional themes, and symbolic imagery. Randy's brain was dreaming while awake, projecting dream content directly onto his waking perception. The boundary between sleep and consciousness was more than binary. It was fluid, and without sleep to maintain the separation, the two states began bleeding into each other. By day nine, Randy couldn't distinguish between his hallucinations and reality. He became convinced that Dr. Dement was plotting against him. He accused the researchers of being imposters. His paranoid delusions were so convincing that even the people documenting his mental breakdown began questioning their own perceptions. Randy's EEG readings showed something unprecedented. His brain waves were cycling through all four stages of sleep while he remained physically awake and mobile. His neurons were firing in sleep patterns, but his motor cortex kept his body upright and functioning. He had become a walking sleeper, a conscious dreamer, a person experiencing two incompatible states of being simultaneously. When Randy finally slept after 264 hours, he didn't collapse into a coma. He slept for 14 hours and 40 minutes, then woke up completely normal. The hallucinations vanished. The paranoia disappeared. His memory returned. But the Stanford team realized they had documented something extraordinary about human consciousness that nobody talks about. Your brain doesn't need sleep to *function*. Randy proved the human body can operate for weeks without it. What your brain needs sleep for is to maintain the distinction between internal mental reality and external physical reality. Sleep isn't rest for your body. Sleep is a firewall for your mind. Without that firewall, the dream world and waking world merge into a single, indistinguishable experience where hallucinations become as real as the room you're sitting in. Randy recovered completely, but sleep researchers never attempted the experiment again. The ethical implications were too severe. They had accidentally discovered that consciousness is far more fragile than anyone suspected, held together by nothing more than eight hours of unconsciousness every night. Every time you go to sleep, your brain is performing the most critical maintenance operation in human biology. It's rebuilding the wall between dreams and reality. And without that wall, there is no difference.
0:18

In 1964, a 17 year old from San Diego conducted the most dangerous psychology experiment ever attempted by a teenager. Randy Gardner stayed awake for 264 hours (11 days) with: • No stimulants • No caffeine • No medical suppressants And Stanford sleep researchers realized too late they couldn't stop him. What happened inside his brain during those 264 hours rewrote everything we thought we knew about consciousness. By day three, Randy's short term memory had completely collapsed. He couldn't remember starting a sentence by the time he reached the end of it. Researchers would ask him to count backward from 100, and he'd stop at 65, staring blankly, having forgotten the entire concept of numbers. But the terrifying part wasn't the memory loss. Randy's brain began creating a second reality that ran parallel to the real one. He'd have full conversations with people who weren't there. He'd walk to locations that didn't exist. His eyes stayed open, his body kept moving, but his mind was living inside elaborate hallucinations that felt completely real to him. Sleep researchers had predicted cognitive decline. They hadn't predicted that the sleep deprived brain would start *manufacturing* an alternate conscious experience to fill the gap. Dr. William Dement, the Stanford researcher monitoring Randy, discovered something that changed sleep science forever. The hallucinations weren't random. They followed the exact same patterns as REM sleep dreams, complete with narrative arcs, emotional themes, and symbolic imagery. Randy's brain was dreaming while awake, projecting dream content directly onto his waking perception. The boundary between sleep and consciousness was more than binary. It was fluid, and without sleep to maintain the separation, the two states began bleeding into each other. By day nine, Randy couldn't distinguish between his hallucinations and reality. He became convinced that Dr. Dement was plotting against him. He accused the researchers of being imposters. His paranoid delusions were so convincing that even the people documenting his mental breakdown began questioning their own perceptions. Randy's EEG readings showed something unprecedented. His brain waves were cycling through all four stages of sleep while he remained physically awake and mobile. His neurons were firing in sleep patterns, but his motor cortex kept his body upright and functioning. He had become a walking sleeper, a conscious dreamer, a person experiencing two incompatible states of being simultaneously. When Randy finally slept after 264 hours, he didn't collapse into a coma. He slept for 14 hours and 40 minutes, then woke up completely normal. The hallucinations vanished. The paranoia disappeared. His memory returned. But the Stanford team realized they had documented something extraordinary about human consciousness that nobody talks about. Your brain doesn't need sleep to *function*. Randy proved the human body can operate for weeks without it. What your brain needs sleep for is to maintain the distinction between internal mental reality and external physical reality. Sleep isn't rest for your body. Sleep is a firewall for your mind. Without that firewall, the dream world and waking world merge into a single, indistinguishable experience where hallucinations become as real as the room you're sitting in. Randy recovered completely, but sleep researchers never attempted the experiment again. The ethical implications were too severe. They had accidentally discovered that consciousness is far more fragile than anyone suspected, held together by nothing more than eight hours of unconsciousness every night. Every time you go to sleep, your brain is performing the most critical maintenance operation in human biology. It's rebuilding the wall between dreams and reality. And without that wall, there is no difference.

Darshak Rana ⚡️

118,551 görüntüleme • 3 ay önce

I love your observation and it will make me discuss the remarkable adaptations that prevents giraffes from passing out and suffering brain damage when bending to drink water and when standing up. ADAPTATION 1 Did you know that the distance from the giraffe's heart to its brain is about 2 meters or more? That's more than the average humans height! Pumping blood up to that great distance and working against gravity is not a joke! That's where the giraffe's heart comes in. A giraffe's heart is unique in several ways. First, it is quite large, weighing up to 11kg and measuring about 2 feet long, which is necessary to pump blood up the long neck to the brain. Second, it has thick walls to generate enough pressure to overcome gravity and push the blood up to the head. ADAPTATION 2 Now, let's move to the neck. Before discussing the incredible roles the valves in the jugular veins perform, let's look at what can happen without them, and then the solution. Problem I: When the giraffe bends down to drink, blood rushes downward to the head. Gravity pulls a huge volume of blood toward the brain, which could cause dangerously high pressure in the head and potentially burst vessels or cause other damage. Solution: They have one-way valves in the jugular veins (the large veins in the neck). These prevent blood from rushing backward uncontrollably into the head when lowered. These valves help regulate and slow the downward flow, avoiding a massive pressure surge to the brain. Also, the neck veins can act as temporary blood storage unit, storing over 1 litre of blood. This prevents blood from flooding the brain and also reduces the amount of blood returning to the heart. As a result, the heart pumps with lower pressure while the head is lowered. This buffers the high head pressure that gravity would otherwise cause. Problem II: When they raise their head up immediately after drinking, blood pressure drops sharply to the brain. A sudden drop could starve the brain of oxygen, causing fainting. This is similar to but much more extreme than the dizziness some people feel when standing up quickly. Solution: When the giraffe raises its head, that stored blood rushes back to the heart quickly. The heart responds with a strong, high-pressure beat that immediately pushes blood back up to the brain, preventing a dangerous drop in cerebral pressure. Impressive right?!
0:15

I love your observation and it will make me discuss the remarkable adaptations that prevents giraffes from passing out and suffering brain damage when bending to drink water and when standing up. ADAPTATION 1 Did you know that the distance from the giraffe's heart to its brain is about 2 meters or more? That's more than the average humans height! Pumping blood up to that great distance and working against gravity is not a joke! That's where the giraffe's heart comes in. A giraffe's heart is unique in several ways. First, it is quite large, weighing up to 11kg and measuring about 2 feet long, which is necessary to pump blood up the long neck to the brain. Second, it has thick walls to generate enough pressure to overcome gravity and push the blood up to the head. ADAPTATION 2 Now, let's move to the neck. Before discussing the incredible roles the valves in the jugular veins perform, let's look at what can happen without them, and then the solution. Problem I: When the giraffe bends down to drink, blood rushes downward to the head. Gravity pulls a huge volume of blood toward the brain, which could cause dangerously high pressure in the head and potentially burst vessels or cause other damage. Solution: They have one-way valves in the jugular veins (the large veins in the neck). These prevent blood from rushing backward uncontrollably into the head when lowered. These valves help regulate and slow the downward flow, avoiding a massive pressure surge to the brain. Also, the neck veins can act as temporary blood storage unit, storing over 1 litre of blood. This prevents blood from flooding the brain and also reduces the amount of blood returning to the heart. As a result, the heart pumps with lower pressure while the head is lowered. This buffers the high head pressure that gravity would otherwise cause. Problem II: When they raise their head up immediately after drinking, blood pressure drops sharply to the brain. A sudden drop could starve the brain of oxygen, causing fainting. This is similar to but much more extreme than the dizziness some people feel when standing up quickly. Solution: When the giraffe raises its head, that stored blood rushes back to the heart quickly. The heart responds with a strong, high-pressure beat that immediately pushes blood back up to the brain, preventing a dangerous drop in cerebral pressure. Impressive right?!

Arojinle

33,422 görüntüleme • 5 ay önce

68 college students played video games an hour a day for 30 weeks. They got measurably smarter. EEG brain scans confirmed it. The setup was simple. Half the group played League of Legends, an action game. The other half played Legends of the Three Kingdoms, a strategy card game. Same hours, same schedule, no gaming experience for anyone going in. Both groups improved on attention, working memory, and executive function. The League group's gains were significantly larger in spatial attention and spatial working memory. The benefits were still measurable 10 weeks after the gaming stopped. None of this is new. Daphne Bavelier's lab at the University of Geneva has been replicating this finding since the early 2000s. Her 2018 meta-analysis in Psychological Bulletin pulled data from 8,970 participants across 15 years and found the same thing. Action games train attentional control, a brain skill that transfers to other tasks. Strategy games train deliberation, which mostly stays inside the strategy game. The mechanism is the counterintuitive part. Action games train your brain by giving you no time to think. The brain can't deliberate. League of Legends throws 9 champions, hundreds of minions, dozens of abilities, mana, cooldowns, and map state at you, all updating in milliseconds. The brain learns to perceive faster instead. That perceptual speed transfers to anything else that demands the same skill. Including surgery. The 2007 Rosser study in Archives of Surgery found that laparoscopic surgeons who played video games more than 3 hours a week made 37% fewer errors, completed procedures 27% faster, and scored 42% higher on overall performance. The top third of gamers made 47% fewer errors. Laparoscopic surgery is a 2D screen with distorted depth perception, remote-controlled instruments, and multiple data streams updating in real time. The cognitive profile is almost identical to an action video game. The 10-week persistence is the part that should change how this gets discussed. If the gains were just from practicing the game, they would have disappeared the moment the students stopped playing. They didn't. The 30 weeks rewired the perceptual system, and the rewiring stayed.
0:19

68 college students played video games an hour a day for 30 weeks. They got measurably smarter. EEG brain scans confirmed it. The setup was simple. Half the group played League of Legends, an action game. The other half played Legends of the Three Kingdoms, a strategy card game. Same hours, same schedule, no gaming experience for anyone going in. Both groups improved on attention, working memory, and executive function. The League group's gains were significantly larger in spatial attention and spatial working memory. The benefits were still measurable 10 weeks after the gaming stopped. None of this is new. Daphne Bavelier's lab at the University of Geneva has been replicating this finding since the early 2000s. Her 2018 meta-analysis in Psychological Bulletin pulled data from 8,970 participants across 15 years and found the same thing. Action games train attentional control, a brain skill that transfers to other tasks. Strategy games train deliberation, which mostly stays inside the strategy game. The mechanism is the counterintuitive part. Action games train your brain by giving you no time to think. The brain can't deliberate. League of Legends throws 9 champions, hundreds of minions, dozens of abilities, mana, cooldowns, and map state at you, all updating in milliseconds. The brain learns to perceive faster instead. That perceptual speed transfers to anything else that demands the same skill. Including surgery. The 2007 Rosser study in Archives of Surgery found that laparoscopic surgeons who played video games more than 3 hours a week made 37% fewer errors, completed procedures 27% faster, and scored 42% higher on overall performance. The top third of gamers made 47% fewer errors. Laparoscopic surgery is a 2D screen with distorted depth perception, remote-controlled instruments, and multiple data streams updating in real time. The cognitive profile is almost identical to an action video game. The 10-week persistence is the part that should change how this gets discussed. If the gains were just from practicing the game, they would have disappeared the moment the students stopped playing. They didn't. The 30 weeks rewired the perceptual system, and the rewiring stayed.

Aakash Gupta

1,417,389 görüntüleme • 3 ay önce

This is the second of two posts I’m making about the teaching of Andy Stanley because I have a burden to warn people to be like the Bereans "examining the Scriptures daily to see if these things were so." (Acts 17:11). I have attached a short video clip where Stanley says we don’t know Jesus rose from the dead because the bible tells us so. He says it’s the other way around. Now how do we know Jesus bodily rose from the dead? Did any of us see it happen? No, it happened 2000 years ago. But haven’t people researched the resurrection and found all sorts of evidence consistent with Him rising from the dead. Yes, but such evidence, though powerful, and we can certainly use in our witnessing, does not ultimately prove He rose from the dead. In fact, no matter what evidence we point to in geology, biology, astronomy etc., none of this proves in an ultimate sense the bible is true. Now it is certainly true such evidence properly interpreted does confirm the bible’s history. For instance, the molecule of heredity DNA is a complex information system and language system. No one has seen matter produce information or a language from matter by natural processes. Our observations and experience show information and language have to come from an intelligence. Such evidence confirms an intelligence behind life. This certainly confirms the first verse of the bible, “In the beginning God created… .” But nonetheless, it’s not absolute proof. Think about it. We are finite beings living in the present. We don’t know everything. We don’t know how much we don’t know or do know in relation to whatever there is to know! When we try to interpret evidence of the present in relation to the past, how do we know we have all the relevant information to make the correct interpretation. Some information we don’t have could totally change our interpretation. That has certainly happened with scientists solving crimes using circumstantial evidence. When new evidence comes along, some of the interpretations change and certain people thought to be guilty were found they were innocent after-all. We need to have all the information needed. But we can’t know everything. However we have a book that claims over three thousand times to be the Word of God. This book claims that God moved people by His spirit to write His Word, what He wants revealed to us about life, the universe and history. This book, the bible, tells us that God knows everything, He is infinite in knowledge and wisdom. He has all information. “In whom are hidden all the treasures of wisdom and knowledge” (Colossians 2:3). If God’s Word is what it claims to be (and it is), then the infinite Creator God has revealed to us the key information we need to know to have the ability to correctly interpret this world in relation to the past, present and its purpose and meaning. “Therefore, we never stop thanking God that when you received his message from us, you didn’t think of our words as mere human ideas. You accepted what we said as the very word of God—which, of course, it is. And this word continues to work in you who believe” (1 Thessalonians 2:13). This means if we build our thinking on God’s Word, we build a Christian worldview to enable us to look at the world through “biblical glasses” and have the ability to correctly interpret and understand it. And Genesis 1-11 is the history that is foundational to the rest of the bible and thus our worldview. So, when we start with God’s Word we learn that the God revealed to us in the bible is the One Who created all things. Now by just looking at the world, for instance at DNA, we might deduce that there’s an intelligence behind life. But we would not know who that intelligence is unless revealed to us. The bible reveals who that intelligence is, God the father, Son, and Holy Spirit. But, if we just looked at the world with all its death, suffering and disease, we could assume that the intelligence behind life must be an ogre to make such a violent disease ridden suffering world. But when we start from God’s Word, we understand there was no death or disease to start with, but these entered the world because of sin. We also find man has a problem called sin which alienated him from God. We even find in Genesis that God promised someone would come to save us from our sin and restore our relationship with God (Genesis 3:15; 3:21). We learn later on that “someone” is Jesus--the one who became flesh for us, the babe in a manger 2000 years ago. It's important to understand we can’t know anything absolutely unless an absolute authority has revealed to us what we need to know. Now Andy Stanley claims we don’t know Jesus rose from the dead because the bible tells us so, but claims it’s the other way round, that because Jesus rose from the dead, we can believe what is says about this in the bible. In reality, Andy Stanley is actually claiming he knows all information about the resurrection to know it’s true so then he can proclaim what the bible says about the resurrection is true. This is not so. And remember from the previous post, Andy Stanley accepts man’s view of evolution and millions of years as true to declare what Genesis records about creation is not all true. So why shouldn't people take the word of others who claim Jesus didn't rise from the dead to then declare the account of the resurrection in the gospels can't be true. Stanley, as a finite fallen human being with very limited knowledge, starts outside the bible to go to the bible to make pronouncements over God’s written Word. No wonder he rejects a literal Genesis. Sadly, this is the case for the majority of our church leaders and Christian academics, particularly when it comes to Genesis. Think about it. Really Stanley is acting in accord with our sin nature because of what happened in Genesis 3. Part of our sin nature concerns us wanting to be our own god. Consider Genesis 3:1 and Genesis 3:5, the temptation by the devil. Satan tempted Adam and Eve to question God’s Word, and be want to be like God to decide good and evil, truth, etc., for themselves. In actuality, the statements Andy Stanley is making about Christianity and God’s Word are reflecting this sin problem we have. He is letting his sin nature master over him in this instance instead of letting God’s Word tell us clearly what we should believe. And I would say that about all Christians who reinterpret parts of the bible (like Genesis) because of beliefs from outside the bible. Now the whole bible is actually about Jesus, from the very first verse, that Jesus is the Creator (Colossians 1:16 “For by him all things were created,”), & and he is the Savior (Revelation 5:9), to the very last verse, “He who testifies to these things says, “Surely I am coming soon.” Amen. Come, Lord Jesus! The grace of the Lord Jesus be with all. Amen” (Revelation 22:20–21) God reveals all we need to know about Jesus in His Word. We know Jesus rose from the dead because the bible tells us so! We know we are sinners because the bible tells us so. We know we can be saved through faith in Christ because the bible tells us so. We know we need to repent of sin because the bible tells us so. As Christians we know we will spend eternity in Heaven because the bible tells us so. “So faith comes from hearing, and hearing through the word of God” (Romans 10:17). I still remember singing the chorus as a child Jesus loves me this I know, for the bible tells me so. Yes, the bible tells me so – that’s how know who Jesus is, that He is the Creator, that he died and rose from the dead, and that He is our Savior.
0:14

This is the second of two posts I’m making about the teaching of Andy Stanley because I have a burden to warn people to be like the Bereans "examining the Scriptures daily to see if these things were so." (Acts 17:11). I have attached a short video clip where Stanley says we don’t know Jesus rose from the dead because the bible tells us so. He says it’s the other way around. Now how do we know Jesus bodily rose from the dead? Did any of us see it happen? No, it happened 2000 years ago. But haven’t people researched the resurrection and found all sorts of evidence consistent with Him rising from the dead. Yes, but such evidence, though powerful, and we can certainly use in our witnessing, does not ultimately prove He rose from the dead. In fact, no matter what evidence we point to in geology, biology, astronomy etc., none of this proves in an ultimate sense the bible is true. Now it is certainly true such evidence properly interpreted does confirm the bible’s history. For instance, the molecule of heredity DNA is a complex information system and language system. No one has seen matter produce information or a language from matter by natural processes. Our observations and experience show information and language have to come from an intelligence. Such evidence confirms an intelligence behind life. This certainly confirms the first verse of the bible, “In the beginning God created… .” But nonetheless, it’s not absolute proof. Think about it. We are finite beings living in the present. We don’t know everything. We don’t know how much we don’t know or do know in relation to whatever there is to know! When we try to interpret evidence of the present in relation to the past, how do we know we have all the relevant information to make the correct interpretation. Some information we don’t have could totally change our interpretation. That has certainly happened with scientists solving crimes using circumstantial evidence. When new evidence comes along, some of the interpretations change and certain people thought to be guilty were found they were innocent after-all. We need to have all the information needed. But we can’t know everything. However we have a book that claims over three thousand times to be the Word of God. This book claims that God moved people by His spirit to write His Word, what He wants revealed to us about life, the universe and history. This book, the bible, tells us that God knows everything, He is infinite in knowledge and wisdom. He has all information. “In whom are hidden all the treasures of wisdom and knowledge” (Colossians 2:3). If God’s Word is what it claims to be (and it is), then the infinite Creator God has revealed to us the key information we need to know to have the ability to correctly interpret this world in relation to the past, present and its purpose and meaning. “Therefore, we never stop thanking God that when you received his message from us, you didn’t think of our words as mere human ideas. You accepted what we said as the very word of God—which, of course, it is. And this word continues to work in you who believe” (1 Thessalonians 2:13). This means if we build our thinking on God’s Word, we build a Christian worldview to enable us to look at the world through “biblical glasses” and have the ability to correctly interpret and understand it. And Genesis 1-11 is the history that is foundational to the rest of the bible and thus our worldview. So, when we start with God’s Word we learn that the God revealed to us in the bible is the One Who created all things. Now by just looking at the world, for instance at DNA, we might deduce that there’s an intelligence behind life. But we would not know who that intelligence is unless revealed to us. The bible reveals who that intelligence is, God the father, Son, and Holy Spirit. But, if we just looked at the world with all its death, suffering and disease, we could assume that the intelligence behind life must be an ogre to make such a violent disease ridden suffering world. But when we start from God’s Word, we understand there was no death or disease to start with, but these entered the world because of sin. We also find man has a problem called sin which alienated him from God. We even find in Genesis that God promised someone would come to save us from our sin and restore our relationship with God (Genesis 3:15; 3:21). We learn later on that “someone” is Jesus--the one who became flesh for us, the babe in a manger 2000 years ago. It's important to understand we can’t know anything absolutely unless an absolute authority has revealed to us what we need to know. Now Andy Stanley claims we don’t know Jesus rose from the dead because the bible tells us so, but claims it’s the other way round, that because Jesus rose from the dead, we can believe what is says about this in the bible. In reality, Andy Stanley is actually claiming he knows all information about the resurrection to know it’s true so then he can proclaim what the bible says about the resurrection is true. This is not so. And remember from the previous post, Andy Stanley accepts man’s view of evolution and millions of years as true to declare what Genesis records about creation is not all true. So why shouldn't people take the word of others who claim Jesus didn't rise from the dead to then declare the account of the resurrection in the gospels can't be true. Stanley, as a finite fallen human being with very limited knowledge, starts outside the bible to go to the bible to make pronouncements over God’s written Word. No wonder he rejects a literal Genesis. Sadly, this is the case for the majority of our church leaders and Christian academics, particularly when it comes to Genesis. Think about it. Really Stanley is acting in accord with our sin nature because of what happened in Genesis 3. Part of our sin nature concerns us wanting to be our own god. Consider Genesis 3:1 and Genesis 3:5, the temptation by the devil. Satan tempted Adam and Eve to question God’s Word, and be want to be like God to decide good and evil, truth, etc., for themselves. In actuality, the statements Andy Stanley is making about Christianity and God’s Word are reflecting this sin problem we have. He is letting his sin nature master over him in this instance instead of letting God’s Word tell us clearly what we should believe. And I would say that about all Christians who reinterpret parts of the bible (like Genesis) because of beliefs from outside the bible. Now the whole bible is actually about Jesus, from the very first verse, that Jesus is the Creator (Colossians 1:16 “For by him all things were created,”), & and he is the Savior (Revelation 5:9), to the very last verse, “He who testifies to these things says, “Surely I am coming soon.” Amen. Come, Lord Jesus! The grace of the Lord Jesus be with all. Amen” (Revelation 22:20–21) God reveals all we need to know about Jesus in His Word. We know Jesus rose from the dead because the bible tells us so! We know we are sinners because the bible tells us so. We know we can be saved through faith in Christ because the bible tells us so. We know we need to repent of sin because the bible tells us so. As Christians we know we will spend eternity in Heaven because the bible tells us so. “So faith comes from hearing, and hearing through the word of God” (Romans 10:17). I still remember singing the chorus as a child Jesus loves me this I know, for the bible tells me so. Yes, the bible tells me so – that’s how know who Jesus is, that He is the Creator, that he died and rose from the dead, and that He is our Savior.

Ken Ham

233,976 görüntüleme • 3 yıl önce

Your brain has a circuit that doesn't know you live in a city. Its only job is to monitor whether birds are still singing. Right now, in this room, it is on. The circuit predates primates. Mammals have been using ambient soundscape continuity as a predator-detection system for roughly 200 million years. Birds stop singing when something larger moves through their territory. For most of mammalian history, a forest full of song meant no large predator was nearby, and the cessation of sound was the warning. Your nervous system never updated this software. The Max Planck Institute tested the inverse in 2022 with 295 participants. Six minutes of birdsong dropped anxiety with a medium effect size. Six minutes of traffic noise raised depression with the same. The effect worked on subjects who lived in dense urban environments and had no regular contact with nature. The brain still ran the check. Birdsong sits in the 1,000 to 8,000 Hz range. Your brainstem reads continuous patterns in that band as a signal that nothing dangerous is currently moving through the environment. EEG data shows birdsong at 45 to 50 decibels boosts alpha wave activity by 14.1% relative to silence. Alpha is the brainwave signature of relaxed alertness. Push the same birdsong above 60 decibels and the response flips. Stress markers rise 29%. The circuit only trusts the signal at the volume of quiet conversation, which is exactly the volume birds sing at from a typical distance. Three things happen simultaneously when the brain registers ambient safety. The amygdala downregulates. The parasympathetic nervous system takes over from the sympathetic. Heart rate variability rises, cortisol drops. The posterior cingulate cortex, which sits at the center of the rumination circuit, quiets down. King's College London tracked this through a smartphone study with over 1,200 participants and found the mood lift lasted hours after the sound stopped. People diagnosed with depression got the same response as healthy controls. Most of what gets labeled mental fatigue is hypervigilance running in the background. Birdsong tells the circuit it can stand down, and the brain reallocates the freed compute everywhere else. A quiet park feels different from a quiet office because the parks have sentinels.
0:15

Your brain has a circuit that doesn't know you live in a city. Its only job is to monitor whether birds are still singing. Right now, in this room, it is on. The circuit predates primates. Mammals have been using ambient soundscape continuity as a predator-detection system for roughly 200 million years. Birds stop singing when something larger moves through their territory. For most of mammalian history, a forest full of song meant no large predator was nearby, and the cessation of sound was the warning. Your nervous system never updated this software. The Max Planck Institute tested the inverse in 2022 with 295 participants. Six minutes of birdsong dropped anxiety with a medium effect size. Six minutes of traffic noise raised depression with the same. The effect worked on subjects who lived in dense urban environments and had no regular contact with nature. The brain still ran the check. Birdsong sits in the 1,000 to 8,000 Hz range. Your brainstem reads continuous patterns in that band as a signal that nothing dangerous is currently moving through the environment. EEG data shows birdsong at 45 to 50 decibels boosts alpha wave activity by 14.1% relative to silence. Alpha is the brainwave signature of relaxed alertness. Push the same birdsong above 60 decibels and the response flips. Stress markers rise 29%. The circuit only trusts the signal at the volume of quiet conversation, which is exactly the volume birds sing at from a typical distance. Three things happen simultaneously when the brain registers ambient safety. The amygdala downregulates. The parasympathetic nervous system takes over from the sympathetic. Heart rate variability rises, cortisol drops. The posterior cingulate cortex, which sits at the center of the rumination circuit, quiets down. King's College London tracked this through a smartphone study with over 1,200 participants and found the mood lift lasted hours after the sound stopped. People diagnosed with depression got the same response as healthy controls. Most of what gets labeled mental fatigue is hypervigilance running in the background. Birdsong tells the circuit it can stand down, and the brain reallocates the freed compute everywhere else. A quiet park feels different from a quiet office because the parks have sentinels.

Aakash Gupta

3,329,469 görüntüleme • 3 ay önce

Omega Programming: Omega programming is self-destruct programming designed as the last line of defense to prevent information leaks. This is one of the most critical components of maintaining plausible deniability when it comes to utilizing Lone Wolf Assets Sleeper Cells. Once Assets are activated, discovered, and/or become disillusioned with their Mission or Handler... they present both direct (kinetic) and indirect (exposure) threats. Activation may be in sequence following orders in a final kamikaze¹ type mission... or may be set as a fail-safe in the event of unauthorized information access and/or transfer. Triggers for activation will be implanted / imprinted / embedded while the subject is put under a somnambulistic level of clinical hypnosis, a process assisted by administration of substances and then supplemented with technology such as Transcranial (Electro)Magnetic Stimulation (TMS). Functional Magnetic Resonance Imaging (fMRI) may be used for real time monitoring in conjunction with/while TMS is used to target portions of the brain such as the Temporal Lobe to elicit "vivd imagery, and the emotional commitment / sensation that something is profound, real, cosmically real, and personally significant." TMS is utilized to send "words as magnetic patterns, and even though the person isn't hearing it through their ears, their brain is interpreting it, so they're actually having fragments of experiences, as if they're hearing it when in actual fact, they cannot be. These experiences are so strong they're utterly real for the person who has them". The Wernicke's area² in the brain - the region responsible for language comprehension - is largely targeted while transmitting these 'words as magnetic patterns' in form of complete programming scripts, essentially. Scripts not only in the sense of a computer programming script... but also a 'screenplay' script, if you will. These scripts are cleverly personalized and written in an Ericksonian³ fashion to go along with and be accepted deep into the subjects psyche. All the while fMRI is utilized to monitor neuron pathways / neural networks / overall brain state and activity... analyzing and evaluating to ensure the programming is anchored into the psyche. There are thresholds and tests upon completion of a 'session'. The first 3 clips are from the 90s while Persinger⁴ was working on an early versions of this technology. Note his mention of this technology being a double edged sword, warning that "you can control people's experiences, and they don't know they are being controlled". The 4th clip is from a lecture of his in 2007... a little more openly hinting to the public at whats been going on behind the scenes. It is VITAL that the public understand Behavior Modification, Omega Programming, and the involved Technology Tradecraft, especially as it relates to Contemporary Issues and Current Events ¹ ² ³ ⁴ (🧵 on Persinger/'s Work)
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Omega Programming: Omega programming is self-destruct programming designed as the last line of defense to prevent information leaks. This is one of the most critical components of maintaining plausible deniability when it comes to utilizing Lone Wolf Assets Sleeper Cells. Once Assets are activated, discovered, and/or become disillusioned with their Mission or Handler... they present both direct (kinetic) and indirect (exposure) threats. Activation may be in sequence following orders in a final kamikaze¹ type mission... or may be set as a fail-safe in the event of unauthorized information access and/or transfer. Triggers for activation will be implanted / imprinted / embedded while the subject is put under a somnambulistic level of clinical hypnosis, a process assisted by administration of substances and then supplemented with technology such as Transcranial (Electro)Magnetic Stimulation (TMS). Functional Magnetic Resonance Imaging (fMRI) may be used for real time monitoring in conjunction with/while TMS is used to target portions of the brain such as the Temporal Lobe to elicit "vivd imagery, and the emotional commitment / sensation that something is profound, real, cosmically real, and personally significant." TMS is utilized to send "words as magnetic patterns, and even though the person isn't hearing it through their ears, their brain is interpreting it, so they're actually having fragments of experiences, as if they're hearing it when in actual fact, they cannot be. These experiences are so strong they're utterly real for the person who has them". The Wernicke's area² in the brain - the region responsible for language comprehension - is largely targeted while transmitting these 'words as magnetic patterns' in form of complete programming scripts, essentially. Scripts not only in the sense of a computer programming script... but also a 'screenplay' script, if you will. These scripts are cleverly personalized and written in an Ericksonian³ fashion to go along with and be accepted deep into the subjects psyche. All the while fMRI is utilized to monitor neuron pathways / neural networks / overall brain state and activity... analyzing and evaluating to ensure the programming is anchored into the psyche. There are thresholds and tests upon completion of a 'session'. The first 3 clips are from the 90s while Persinger⁴ was working on an early versions of this technology. Note his mention of this technology being a double edged sword, warning that "you can control people's experiences, and they don't know they are being controlled". The 4th clip is from a lecture of his in 2007... a little more openly hinting to the public at whats been going on behind the scenes. It is VITAL that the public understand Behavior Modification, Omega Programming, and the involved Technology Tradecraft, especially as it relates to Contemporary Issues and Current Events ¹ ² ³ ⁴ (🧵 on Persinger/'s Work)

Grey

20,921 görüntüleme • 1 yıl önce

Why did the Israeli defense minister say: "we are fighting human animals"? You may think it is because of earlier atrocities, but it is not Few know this, but the Jewish oral tradition, the Talmud, states that all non-jews are animals in human form built only to serve the Jews in a more respectable manner than a four-legged beast. What makes a Jew a Jew is their obedience to the Talmud, not the Old Testament, this is a common misconception. Just like the Pharisees with their traditions of men, the Talmud is a legalistic workaround all of God's OT laws. Mark 7:13: "Making the word of God of none effect through your tradition, which ye have delivered: and many such like things do ye" Unfortunately, many modern Christians have devolved into blatant Pharisee worship, even elevating the flag of the Pharisees 🇮🇱 with the cross of our Lord ✝️ pledging their undying support to the Pharisee cause. There is a difference though the oral tradition of today is even worse than at the time of the crucifixion and now allows, by their religious law, theft, cheating, murder of non-jews, and even pedophilia. There is a very small community (40,000 worldwide) of Kararite Jews that actually do worship the OT exclusively, but they are horribly discriminated against and were banned from entering Israel by official diktat until only recently in 2007. To this day, they are still hated in Israel for choosing (half) of the Word of God over the man-made traditions of the Pharisees.
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Why did the Israeli defense minister say: "we are fighting human animals"? You may think it is because of earlier atrocities, but it is not Few know this, but the Jewish oral tradition, the Talmud, states that all non-jews are animals in human form built only to serve the Jews in a more respectable manner than a four-legged beast. What makes a Jew a Jew is their obedience to the Talmud, not the Old Testament, this is a common misconception. Just like the Pharisees with their traditions of men, the Talmud is a legalistic workaround all of God's OT laws. Mark 7:13: "Making the word of God of none effect through your tradition, which ye have delivered: and many such like things do ye" Unfortunately, many modern Christians have devolved into blatant Pharisee worship, even elevating the flag of the Pharisees 🇮🇱 with the cross of our Lord ✝️ pledging their undying support to the Pharisee cause. There is a difference though the oral tradition of today is even worse than at the time of the crucifixion and now allows, by their religious law, theft, cheating, murder of non-jews, and even pedophilia. There is a very small community (40,000 worldwide) of Kararite Jews that actually do worship the OT exclusively, but they are horribly discriminated against and were banned from entering Israel by official diktat until only recently in 2007. To this day, they are still hated in Israel for choosing (half) of the Word of God over the man-made traditions of the Pharisees.

Politics Is Masonic Theater: 🍞 & 🎪

193,529 görüntüleme • 2 yıl önce

Learning is something you and your baby do together. You can think of the process as happening in three distinct stages, during which skills are transferred gradually from you to your little one: During the first stage, your baby is observing the behavior and skills of others. During the second, they begin to emulate these behaviors - and can find success with the support of a helpful adult (you) or more expert peer (often a sibling). And gradually they internalize these skills and perform them all by themselves. This video is a great example of the shared second phase. Infants explore the world with their mouths. But an important lesson of toddlerhood is that some things are for putting in our mouths, while others are not. This little one knows that we don’t eat the Play-Doh. But it sure is tempting! Watch as he breaks off a piece and brings it to his mouth. As he does his eyes lift and he realizes that Mom is watching - which alone prompts some introspection. He grins broadly, shakes his head and exclaims “No, no, no” - using Mom’s past words to affirm his decision to place the Play-Doh back on the table. Left to his own devices, who knows? But together, without exchanging a word, he managed to make the right choice. As a parent it’s important to remember the key role you play in the learning process. And that extends to your child’s behavior. Self-regulation begins as co-regulation. So be there. This sweet little guy was shared to IG by parentosa.
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Learning is something you and your baby do together. You can think of the process as happening in three distinct stages, during which skills are transferred gradually from you to your little one: During the first stage, your baby is observing the behavior and skills of others. During the second, they begin to emulate these behaviors - and can find success with the support of a helpful adult (you) or more expert peer (often a sibling). And gradually they internalize these skills and perform them all by themselves. This video is a great example of the shared second phase. Infants explore the world with their mouths. But an important lesson of toddlerhood is that some things are for putting in our mouths, while others are not. This little one knows that we don’t eat the Play-Doh. But it sure is tempting! Watch as he breaks off a piece and brings it to his mouth. As he does his eyes lift and he realizes that Mom is watching - which alone prompts some introspection. He grins broadly, shakes his head and exclaims “No, no, no” - using Mom’s past words to affirm his decision to place the Play-Doh back on the table. Left to his own devices, who knows? But together, without exchanging a word, he managed to make the right choice. As a parent it’s important to remember the key role you play in the learning process. And that extends to your child’s behavior. Self-regulation begins as co-regulation. So be there. This sweet little guy was shared to IG by parentosa.

Dan Wuori

75,169 görüntüleme • 2 yıl önce

Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!
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Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!

Akshay 🚀

126,122 görüntüleme • 9 ay önce

Grok Summary of Neuralink’s “Two Years of Telepathy” Update Neuralink’s Telepathy is their pioneering brain-computer interface (BCI) aimed at restoring independence for people with paralysis by translating neural signals into digital commands for controlling devices like computers, phones, and robotic limbs. The article reflects on two years of progress, highlighting clinical trials with 21 participants (Neuralnauts), technical breakthroughs, personal stories of transformation, challenges, and ambitious future goals. • Key Milestones: Enrolled 21 participants worldwide; achieved information transfer rates over 10 bits per second (surpassing able-bodied mouse control); developed a mental ten-finger keyboard for typing up to 40 words per minute; launched the VOICE trial for real-time speech restoration targeting 140 words per minute; expanded trials from three in 2024 to multiple per month in 2025, with no serious device-related adverse events. • Patient Experiences and Impacts: ◦ Noland (first recipient, spinal cord injury): Regained independence for studying, reading, and college (best grades ever); describes it as reclaiming lost life. ◦Nick (paralyzed four years): Controls robotic arm for tasks like feeding; feels natural gestures, restoring a sense of movement. ◦Sebastian (medical student, recent injury): Uses for 17 hours daily to annotate papers and multitask in lectures, boosting productivity. ◦Audrey (20-year injury): Creates abstract art, gains online fame, plans a gallery; feels her mind “a little free.” ◦Jake (ALS): Uses mental keyboard for tasks; sees himself as a “superhero” for his son. ◦Brad (ALS): Controls wheelchair camera to watch his son at events; views ALS as an opportunity for innovation. • Technical Advancements: Translates thoughts into intuitive cursor/robotic control; detects bilateral hand signals from single-sided implants; adapts to individual brain variations during surgery; upcoming upgrades include tripling electrodes to 3000 and exploring less invasive insertion methods. • Challenges: Variations in brain anatomy and disease stages affect performance; early thread retraction issues addressed; communication loss in ALS patients (up to 95% decline ventilation); need for faster, more natural control. • Future Plans: Enhance hardware and procedures for consistency; advance speech restoration; accelerate enrollments; invite quadriplegic individuals (from spinal cord injury, ALS, or stroke) to join the patient registry; seek talent to scale solutions.
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Grok Summary of Neuralink’s “Two Years of Telepathy” Update Neuralink’s Telepathy is their pioneering brain-computer interface (BCI) aimed at restoring independence for people with paralysis by translating neural signals into digital commands for controlling devices like computers, phones, and robotic limbs. The article reflects on two years of progress, highlighting clinical trials with 21 participants (Neuralnauts), technical breakthroughs, personal stories of transformation, challenges, and ambitious future goals. • Key Milestones: Enrolled 21 participants worldwide; achieved information transfer rates over 10 bits per second (surpassing able-bodied mouse control); developed a mental ten-finger keyboard for typing up to 40 words per minute; launched the VOICE trial for real-time speech restoration targeting 140 words per minute; expanded trials from three in 2024 to multiple per month in 2025, with no serious device-related adverse events. • Patient Experiences and Impacts: ◦ Noland (first recipient, spinal cord injury): Regained independence for studying, reading, and college (best grades ever); describes it as reclaiming lost life. ◦Nick (paralyzed four years): Controls robotic arm for tasks like feeding; feels natural gestures, restoring a sense of movement. ◦Sebastian (medical student, recent injury): Uses for 17 hours daily to annotate papers and multitask in lectures, boosting productivity. ◦Audrey (20-year injury): Creates abstract art, gains online fame, plans a gallery; feels her mind “a little free.” ◦Jake (ALS): Uses mental keyboard for tasks; sees himself as a “superhero” for his son. ◦Brad (ALS): Controls wheelchair camera to watch his son at events; views ALS as an opportunity for innovation. • Technical Advancements: Translates thoughts into intuitive cursor/robotic control; detects bilateral hand signals from single-sided implants; adapts to individual brain variations during surgery; upcoming upgrades include tripling electrodes to 3000 and exploring less invasive insertion methods. • Challenges: Variations in brain anatomy and disease stages affect performance; early thread retraction issues addressed; communication loss in ALS patients (up to 95% decline ventilation); need for faster, more natural control. • Future Plans: Enhance hardware and procedures for consistency; advance speech restoration; accelerate enrollments; invite quadriplegic individuals (from spinal cord injury, ALS, or stroke) to join the patient registry; seek talent to scale solutions.

DogeDesigner

17,651 görüntüleme • 6 ay önce

THE DEPTH MAP TRICK THAT FIXED DANCE ACCURACY IN SEEDANCE 2.0 Feed the model a video of someone dancing and it tries to interpret everything- the person, the clothes, the lighting, the room, and somewhere in there, the movement. Feed it a depth map and there's nothing left to interpret but the motion. Most creators trying to transfer a dance to a character reference the source footage directly, then wonder why the choreography drifts. The problem isn't the model - it's that you handed it ten variables when you only wanted one. Here's the workflow 1. Lock the character reference in GPT Image 2 first -face, build, costume, so identity holds independently of whatever motion gets applied to it 2. Convert the source dance footage into a depth map instead of using the raw video -this strips out the original performer's appearance, clothing, and environment entirely 3. Feed the depth map as the motion reference and the character sheet as the identity reference- two separate inputs doing two separate jobs, not one input trying to do both 5. Let the depth map carry only spatial movement -the model receives body position and momentum with no competing information about who's moving or what they look like 6. Keep the character and motion inputs isolated throughout - the moment you mix appearance data into the motion reference, the model starts negotiating between two identities Why this works • Raw footage passes the model everything at once- performer, wardrobe, room, lighting -and the choreography competes with all of it for attention • A depth map is pure spatial information, so the only thing left to transfer is movement • Separating identity from motion means the character can stay locked while the dance stays accurate - normally you're trading one for the other • The accuracy gain isn't the model getting better, it's the model getting fewer decisions to make Use cases: ⁃ Dance and choreography transfer onto original characters ⁃ Motion capture-style workflows without motion capture ⁃ Any sequence where a specific movement needs to survive intact ⁃ Character showcase content built on existing performance footage The character sheet answers who's dancing. The depth map answers how - and keeping those two questions separate is the whole trick.
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THE DEPTH MAP TRICK THAT FIXED DANCE ACCURACY IN SEEDANCE 2.0 Feed the model a video of someone dancing and it tries to interpret everything- the person, the clothes, the lighting, the room, and somewhere in there, the movement. Feed it a depth map and there's nothing left to interpret but the motion. Most creators trying to transfer a dance to a character reference the source footage directly, then wonder why the choreography drifts. The problem isn't the model - it's that you handed it ten variables when you only wanted one. Here's the workflow 1. Lock the character reference in GPT Image 2 first -face, build, costume, so identity holds independently of whatever motion gets applied to it 2. Convert the source dance footage into a depth map instead of using the raw video -this strips out the original performer's appearance, clothing, and environment entirely 3. Feed the depth map as the motion reference and the character sheet as the identity reference- two separate inputs doing two separate jobs, not one input trying to do both 5. Let the depth map carry only spatial movement -the model receives body position and momentum with no competing information about who's moving or what they look like 6. Keep the character and motion inputs isolated throughout - the moment you mix appearance data into the motion reference, the model starts negotiating between two identities Why this works • Raw footage passes the model everything at once- performer, wardrobe, room, lighting -and the choreography competes with all of it for attention • A depth map is pure spatial information, so the only thing left to transfer is movement • Separating identity from motion means the character can stay locked while the dance stays accurate - normally you're trading one for the other • The accuracy gain isn't the model getting better, it's the model getting fewer decisions to make Use cases: ⁃ Dance and choreography transfer onto original characters ⁃ Motion capture-style workflows without motion capture ⁃ Any sequence where a specific movement needs to survive intact ⁃ Character showcase content built on existing performance footage The character sheet answers who's dancing. The depth map answers how - and keeping those two questions separate is the whole trick.

Nexlow

85,202 görüntüleme • 1 ay önce