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What seemed like an intractable problem is now possible: To design proteins with a specified nonlinear mechanical response, capturing complex folding and unfolding mechanisms in singe and few-shot computations. We present ForceGen, an end-to-end algorithm for de novo protein generation based on nonlinear mechanical unfolding responses. Rooted in the...

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Markus J. Buehler

20,498 subscribers

47,242 次观看 • 2 年前 •via X (Twitter)

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10 条评论

The Guy 的头像
The Guy2 年前

I can imagine someone setting out with a dictionary of all the major cancer causing mutations to find the protein changes they lead to then reverse engineering a "fixer" protein that either marks those cells for destruction or repairs the malfunctioning protein.

Ella Marushchenko 的头像
Ella Marushchenko2 年前

@tamjeeds Congratulations on this fascinating breakthrough! Could ForceGen fast-track the development of self-repairing biomaterials?

Sohm Music 的头像
Sohm Music2 年前

This absolutely has to take the cake, best discovery of the year so far!

Markus Rauhalahti 的头像
Markus Rauhalahti2 年前

Beautiful work! Huge fan of your/group's curiosity towards frameworks and methods, from category theory to the recent LLM explorations. Looking forward to reading this properly and testing it out, thanks for sharing the code and weights!

Markus J. Buehler 的头像
Markus J. Buehler2 年前

Thank you @MRauhalahti !

Gioele Zardini 的头像
Gioele Zardini2 年前

This is amazing Markus, looking forward to discovering more!

Brian Timko Laboratory 的头像
Brian Timko Laboratory2 年前

@KaplanLab_Tufts Very cool!

Jugal 的头像
Jugal2 年前

Congratulations!!

Jason Liu 的头像
Jason Liu2 年前

Congrats! This looks super cool! Did you mean 'single' in "...mechanisms in singe and few-shot computations..." (paragraph 1)?

Ⓜⓐⓡⓖⓘⓝ ⓒⓐⓛⓛ 的头像
Ⓜⓐⓡⓖⓘⓝ ⓒⓐⓛⓛ2 年前

Nice work, similar to AFM.

相关视频

We're thrilled to present ESM3 in Science Magazine. ESM3 is a generative language model that reasons over the three fundamental properties of proteins: sequence, structure, and function. Today we're making ESM3 available free to researchers worldwide via the public beta of an API for biological intelligence. Trained with over a trillion teraflops of compute, this is the first time a model of this scale has been trained for biology, pushing the frontier of AI for biological discovery and engineering. ESM3 learns to represent the immense complexity of protein biology, learning from billions of natural proteins. From this training it developed the capability to design proteins, responding to complex prompts combining atomic level details and high level instructions to generate new proteins. ESM3 can explore protein space far beyond natural evolution. We prompted ESM3 to generate a fluorescent protein at a far distance from any known fluorescent proteins, searching an unknown region of protein space, to discover a new fluorescent protein. We estimate this is equivalent to simulating five hundred million years of evolution.
1:31

We're thrilled to present ESM3 in Science Magazine. ESM3 is a generative language model that reasons over the three fundamental properties of proteins: sequence, structure, and function. Today we're making ESM3 available free to researchers worldwide via the public beta of an API for biological intelligence. Trained with over a trillion teraflops of compute, this is the first time a model of this scale has been trained for biology, pushing the frontier of AI for biological discovery and engineering. ESM3 learns to represent the immense complexity of protein biology, learning from billions of natural proteins. From this training it developed the capability to design proteins, responding to complex prompts combining atomic level details and high level instructions to generate new proteins. ESM3 can explore protein space far beyond natural evolution. We prompted ESM3 to generate a fluorescent protein at a far distance from any known fluorescent proteins, searching an unknown region of protein space, to discover a new fluorescent protein. We estimate this is equivalent to simulating five hundred million years of evolution.

Alex Rives

227,261 次观看 • 1 年前

Can Claude Code design proteins? We're just about to release our wet lab API + SDK so we made a quick demo to test how agents can interact with protein design models and submit the proteins to our lab for testing. This closes the loop between the computational design and the experiment validation We queued up a bunch of agent-designed proteins for wet lab validation, will release the results in a couple weeks on Proteinbase
1:15

Can Claude Code design proteins? We're just about to release our wet lab API + SDK so we made a quick demo to test how agents can interact with protein design models and submit the proteins to our lab for testing. This closes the loop between the computational design and the experiment validation We queued up a bunch of agent-designed proteins for wet lab validation, will release the results in a couple weeks on Proteinbase

Julian Englert

81,258 次观看 • 6 个月前

Proof that Life is Intelligently Designed: Proteins. They do everything in your cells that keeps you alive. These microscopic molecules must have been created. Here is why: Proteins are the building blocks of all the little nano-machines that make up your cells. They do all the major work in your body - from creating energy to recycling waste. Proteins are made from amino acids connected into a specific sequence and then folded into a functional shape. You can think of a protein like a paragraph, and amino acids as the individual letters that spell out the words. Here is where it gets interesting... There are just 20 amino acids used in all of Life. Just 20 amino acids. Responsible for ~200 million unique proteins making up tens of thousands of cell types across Life. And scientists are constantly finding new ones. Scientists categorize proteins into Families. Protein Families are groups of proteins that share amino acid sequence similarities. There are ~22,000 Protein Families. Here's the part that screams they are designed... Protein Families have no evolutionary history. Even evolutionist scientists agree - they are absolutely unique. It's been said that proteins are like stars in a galaxy, and families are like galaxies, with vast empty space between them. Evolution is supposed to build by tweaking things that already exist. But no evolutionary history connects fundamentally distinct protein families. Experiments have been done to intentionally evolve one protein family into another. They fail every time. One protein family cannot be evolved into another. They cannot arise through evolution. But the math really makes it impossible... The odds of evolution finding even a single functional protein family is 1 chance in 10^77 possible amino acid sequences. That's a 1 with 77 zeroes. The odds of evolution finding 22,000 distinct protein families? Roughly 1 chance in 10^1,694,000. You don't need to be a mathematician to understand that this is impossible. Evolution works by random mutations tweaking what's already there. But protein families can't evolve from one another. And the math makes it absolutely absurd to believe. Monkeys banging on keyboards will never type out Shakespeare. And random mutations in sequences of amino acids could never create a single functional protein family. There is only one thing we know of that creates functionally specified sequences: Intelligence. Now here is the final cherry on top: Proteins are built by other proteins, assembled into a complex machine to do a job in cells. The assembly instructions for those proteins and the machines are found in DNA. But DNA requires protein machines for replication & repair. So DNA is required to make Proteins... ...but Proteins are required to make DNA *and* more Proteins. You can't have one without the other. They rely on each other. Which means one couldn't have evolved and then waited for the other. They couldn't do anything without each other. They had to be created at the same time to function together. Life was Divinely Designed. Proteins prove it.
0:38

Proof that Life is Intelligently Designed: Proteins. They do everything in your cells that keeps you alive. These microscopic molecules must have been created. Here is why: Proteins are the building blocks of all the little nano-machines that make up your cells. They do all the major work in your body - from creating energy to recycling waste. Proteins are made from amino acids connected into a specific sequence and then folded into a functional shape. You can think of a protein like a paragraph, and amino acids as the individual letters that spell out the words. Here is where it gets interesting... There are just 20 amino acids used in all of Life. Just 20 amino acids. Responsible for ~200 million unique proteins making up tens of thousands of cell types across Life. And scientists are constantly finding new ones. Scientists categorize proteins into Families. Protein Families are groups of proteins that share amino acid sequence similarities. There are ~22,000 Protein Families. Here's the part that screams they are designed... Protein Families have no evolutionary history. Even evolutionist scientists agree - they are absolutely unique. It's been said that proteins are like stars in a galaxy, and families are like galaxies, with vast empty space between them. Evolution is supposed to build by tweaking things that already exist. But no evolutionary history connects fundamentally distinct protein families. Experiments have been done to intentionally evolve one protein family into another. They fail every time. One protein family cannot be evolved into another. They cannot arise through evolution. But the math really makes it impossible... The odds of evolution finding even a single functional protein family is 1 chance in 10^77 possible amino acid sequences. That's a 1 with 77 zeroes. The odds of evolution finding 22,000 distinct protein families? Roughly 1 chance in 10^1,694,000. You don't need to be a mathematician to understand that this is impossible. Evolution works by random mutations tweaking what's already there. But protein families can't evolve from one another. And the math makes it absolutely absurd to believe. Monkeys banging on keyboards will never type out Shakespeare. And random mutations in sequences of amino acids could never create a single functional protein family. There is only one thing we know of that creates functionally specified sequences: Intelligence. Now here is the final cherry on top: Proteins are built by other proteins, assembled into a complex machine to do a job in cells. The assembly instructions for those proteins and the machines are found in DNA. But DNA requires protein machines for replication & repair. So DNA is required to make Proteins... ...but Proteins are required to make DNA *and* more Proteins. You can't have one without the other. They rely on each other. Which means one couldn't have evolved and then waited for the other. They couldn't do anything without each other. They had to be created at the same time to function together. Life was Divinely Designed. Proteins prove it.

Divinely Designed

18,833 次观看 • 26 天前

NEW EPISODE of HARD DRUGS! AlphaFold, ProteinMPNN and other AI tools are transforming biology and drug design. But how do they work? What can’t they do (yet)? And can we use them to make a vaccine against Strep A for the very first time? In this episode, Jacob and I talk about hacking proteins with AI. 03:21 What makes proteins cool 05:29 Can we make a vaccine against Strep A? 10:12 Proteins in nature aren’t enough, and we can improve them with AI 21:12 ProteinMPNN and AlphaFold are transforming drug design 29:52 A short history of protein structure prediction from physical models to deep learning 34:48 Using AI to design a Strep A vaccine 39:27 Validating an AI-designed Strep A vaccine 43:09 Recent AI protein breakthroughs 49:30 Why we don’t already have a Strep A vaccine and the future of optimizing protein drugs
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NEW EPISODE of HARD DRUGS! AlphaFold, ProteinMPNN and other AI tools are transforming biology and drug design. But how do they work? What can’t they do (yet)? And can we use them to make a vaccine against Strep A for the very first time? In this episode, Jacob and I talk about hacking proteins with AI. 03:21 What makes proteins cool 05:29 Can we make a vaccine against Strep A? 10:12 Proteins in nature aren’t enough, and we can improve them with AI 21:12 ProteinMPNN and AlphaFold are transforming drug design 29:52 A short history of protein structure prediction from physical models to deep learning 34:48 Using AI to design a Strep A vaccine 39:27 Validating an AI-designed Strep A vaccine 43:09 Recent AI protein breakthroughs 49:30 Why we don’t already have a Strep A vaccine and the future of optimizing protein drugs

Saloni

72,565 次观看 • 9 个月前

This is how DNA turns raw data into functional proteins - the building blocks of all your cells. This system requires a minimum of 3 key players working together: DNA: the master blueprint with the instructions RNA Polymerase: reads the DNA and makes a temporary copy called mRNA which carries the instructions to the Ribosome for how to create the Protein Ribosome: the tiny factory that reads the mRNA and strings amino acids together in a specific sequence to create a protein Without all three molecules working together, Proteins cannot be created, cells don't function, and Life ends. Everything needs to fit together, precisely & perfectly, or it all falls apart. In other words: this system cannot evolve, one step at a time. DNA relies other machines made of proteins to create those very proteins - but those proteins can't be made without the information in the DNA. And on top of that, this whole system relies on OTHER systems! You need other things like ATP Synthase that makes energy to power everything, tRNA to carry the amino acids to the Ribosome, other helper proteins, processing enzymes, etc. It's an extremely complex, interdependent network of parts & systems that all rely on each other. The cell is an astounding level of complexity that surpasses anything in human engineering. It's obvious this is intelligently designed. To deny that is absurd.
2:15

This is how DNA turns raw data into functional proteins - the building blocks of all your cells. This system requires a minimum of 3 key players working together: DNA: the master blueprint with the instructions RNA Polymerase: reads the DNA and makes a temporary copy called mRNA which carries the instructions to the Ribosome for how to create the Protein Ribosome: the tiny factory that reads the mRNA and strings amino acids together in a specific sequence to create a protein Without all three molecules working together, Proteins cannot be created, cells don't function, and Life ends. Everything needs to fit together, precisely & perfectly, or it all falls apart. In other words: this system cannot evolve, one step at a time. DNA relies other machines made of proteins to create those very proteins - but those proteins can't be made without the information in the DNA. And on top of that, this whole system relies on OTHER systems! You need other things like ATP Synthase that makes energy to power everything, tRNA to carry the amino acids to the Ribosome, other helper proteins, processing enzymes, etc. It's an extremely complex, interdependent network of parts & systems that all rely on each other. The cell is an astounding level of complexity that surpasses anything in human engineering. It's obvious this is intelligently designed. To deny that is absurd.

Divinely Designed

22,903 次观看 • 6 个月前

This is how DNA turns coded information into functional proteins - the building blocks of the nanomachines that keep the cells in your body alive. This complex process highlights the sophisticated interconnected systems of Life which must all exist together from the beginning, or Life doesn't happen. First, an RNA molecule is copied from a short segment of DNA. Without the specifically ordered DNA information, RNA cannot form, proteins cannot be built, cells stop working, and life ceases to exist. Life is information first. Once the RNA Molecule is created, it gets ejected from the Polymerase where it was built, and it travels through a complex molecular machine called a Nuclear Pore Complex (NPC), which is an information recognition device that controls the flow of information in and out of a cell's nucleus. The NPC is highly complex - composed of about 500-1,000 protein subunits, derived from a set of about 35 distinct proteins. Without this molecular machine, there is no regulation for what goes in and out of the cell's nucleus, which would lead to catastrophic death for the cell. It must exist for cells to exist. Once the RNA Molecule passes through the NPC, it travels to the Ribosome, a 2-part chemical factory which reads the information on RNA and uses it to construct functional proteins using a specifically sequenced chain of amino acids. Once complete, this protein will then be sent to the section of the cell it belongs to integrate into another molecular machine and do its job. The Ribosome is another highly complex molecular machine - consisting of between 56-80 proteins. Without this molecular machines, proteins cannot be built. Proteins are the building blocks of every cell in every organism on Earth. Without Ribosomes, Life doesn't exist. If you're paying attention, you'll start to realize that Life relies on a highly sophisticated interdependent network of complex machines, which all rely on each other for the function of the system. DNA requires the cell for stability, but the cell requires the proteins for its structure and function, but those proteins require DNA and RNA to be built - it's a circle of necessary interdependence. Systems like this cannot be built by evolutionary processes, which requires that each piece of the process is built by gradual incremental means over lots of time. Without all the pieces there, from the beginning, none of it works. There is only one known source of complex & interdependent informational systems like those we find in life: and that is from Intelligence. Molecular Biology is the best and most obvious evidence of the Intelligent Design in Life.
0:55

This is how DNA turns coded information into functional proteins - the building blocks of the nanomachines that keep the cells in your body alive. This complex process highlights the sophisticated interconnected systems of Life which must all exist together from the beginning, or Life doesn't happen. First, an RNA molecule is copied from a short segment of DNA. Without the specifically ordered DNA information, RNA cannot form, proteins cannot be built, cells stop working, and life ceases to exist. Life is information first. Once the RNA Molecule is created, it gets ejected from the Polymerase where it was built, and it travels through a complex molecular machine called a Nuclear Pore Complex (NPC), which is an information recognition device that controls the flow of information in and out of a cell's nucleus. The NPC is highly complex - composed of about 500-1,000 protein subunits, derived from a set of about 35 distinct proteins. Without this molecular machine, there is no regulation for what goes in and out of the cell's nucleus, which would lead to catastrophic death for the cell. It must exist for cells to exist. Once the RNA Molecule passes through the NPC, it travels to the Ribosome, a 2-part chemical factory which reads the information on RNA and uses it to construct functional proteins using a specifically sequenced chain of amino acids. Once complete, this protein will then be sent to the section of the cell it belongs to integrate into another molecular machine and do its job. The Ribosome is another highly complex molecular machine - consisting of between 56-80 proteins. Without this molecular machines, proteins cannot be built. Proteins are the building blocks of every cell in every organism on Earth. Without Ribosomes, Life doesn't exist. If you're paying attention, you'll start to realize that Life relies on a highly sophisticated interdependent network of complex machines, which all rely on each other for the function of the system. DNA requires the cell for stability, but the cell requires the proteins for its structure and function, but those proteins require DNA and RNA to be built - it's a circle of necessary interdependence. Systems like this cannot be built by evolutionary processes, which requires that each piece of the process is built by gradual incremental means over lots of time. Without all the pieces there, from the beginning, none of it works. There is only one known source of complex & interdependent informational systems like those we find in life: and that is from Intelligence. Molecular Biology is the best and most obvious evidence of the Intelligent Design in Life.

Divinely Designed

62,517 次观看 • 6 个月前

The next frontier in protein design will not be defined by structure alone, but by the capacity to engineer motion as a first-class principle of function. This is because dynamics is where the real biology lives. Foundational work by Karplus, Levitt & Warshel made clear that chemistry cannot be understood without motion, mechanism, and scale. Gō, Brooks & others showed that proteins possess characteristic collective motions - low-frequency normal modes that capture how whole molecules bend, breathe, and fluctuate. Frauenfelder then sharpened the picture further: proteins are not static objects occupying a single minimum, but dynamic ensembles traversing rugged energy landscapes. And yet the modern AI revolution in protein science has been, above all, a revolution in structure. In our new paper in Matter, Bo Ni and I ask a different question: not what structure will this sequence adopt? but what sequence will realize a prescribed pattern of motion? VibeGen inverts the conventional design paradigm. Rather than treating dynamics as a consequence to be analyzed after the fact, it makes dynamics the design objective from the outset. Using a language diffusion model with two cooperating agents - a designer that proposes sequences and a predictor that critiques them against the target motion profile - the system converges on de novo proteins with tailored vibrational behavior. One of the most intriguing results is a form of functional degeneracy - distinct sequences and distinct folds can satisfy the same target dynamical specification. For a given functional pattern of motion, evolution may have sampled only a small region of the physically realizable design space. The space of viable molecular mechanics may be far larger than the repertoire biology happened to discover. We have made "vibe" into a cultural metaphor - something intuitive, affective, subjective. But at the molecular scale, vibe is not metaphor: It is physics. For a protein, the vibe is the pattern of motion itself; the fluctuations, resonances, and collective displacements that determine what the molecule can do.
0:52

The next frontier in protein design will not be defined by structure alone, but by the capacity to engineer motion as a first-class principle of function. This is because dynamics is where the real biology lives. Foundational work by Karplus, Levitt & Warshel made clear that chemistry cannot be understood without motion, mechanism, and scale. Gō, Brooks & others showed that proteins possess characteristic collective motions - low-frequency normal modes that capture how whole molecules bend, breathe, and fluctuate. Frauenfelder then sharpened the picture further: proteins are not static objects occupying a single minimum, but dynamic ensembles traversing rugged energy landscapes. And yet the modern AI revolution in protein science has been, above all, a revolution in structure. In our new paper in Matter, Bo Ni and I ask a different question: not what structure will this sequence adopt? but what sequence will realize a prescribed pattern of motion? VibeGen inverts the conventional design paradigm. Rather than treating dynamics as a consequence to be analyzed after the fact, it makes dynamics the design objective from the outset. Using a language diffusion model with two cooperating agents - a designer that proposes sequences and a predictor that critiques them against the target motion profile - the system converges on de novo proteins with tailored vibrational behavior. One of the most intriguing results is a form of functional degeneracy - distinct sequences and distinct folds can satisfy the same target dynamical specification. For a given functional pattern of motion, evolution may have sampled only a small region of the physically realizable design space. The space of viable molecular mechanics may be far larger than the repertoire biology happened to discover. We have made "vibe" into a cultural metaphor - something intuitive, affective, subjective. But at the molecular scale, vibe is not metaphor: It is physics. For a protein, the vibe is the pattern of motion itself; the fluctuations, resonances, and collective displacements that determine what the molecule can do.

Markus J. Buehler

89,620 次观看 • 3 个月前

This is a Kinesin Molecule. These little molecular machines are commonly referred to as the "workhorse" of the cell, hauling important cargo like organelles, proteins and other cellular structures to their proper location within the cell. Kinesins are very clear & undeniable evidence of the intelligent design in Life. Kinesins are complex molecular machines, made up of 4 total proteins, each between 500-1,300 amino acids in length. If these aa sequences are not perfectly aligned from the beginning, Kinesin never forms, and cellular life would be unable to survive. Here is how they work: When a new protein, organelle, or other cellular structure is created in the Cytosol of the cell, they are constructed with built-in "binding tags," which are like shipping labels that bind to other protein molecules called Adaptor or Scaffold Proteins. These Adaptor/Scaffold Proteins then attach to the Kinesin's tail, which activates them, and then the Kinesin is guided along the microtubule track to its to its final destination. Kinesin walk on self-assembling tracks of other proteins, called microtubules, moving cargo from the inner area of the cell where they are constructed to the outer edges where they function. This is a complex & sophisticated interdependent network of molecular machines, all relying on one another to function properly for the health of the cell. This Intracellular Transportation system MUST be fully functional from the beginning - with all these working parts, or all of it fails, and the cell dies. Without this entire functioning system, Life could not exist. And the Kinesin is the centerpiece to all of it. Experiments have shown that disrupting Kinesin activity has catastrophic consequences. This type of nano-precision is an obvious example of designed engineering. Blind, unguided evolutionary processes cannot plan ahead and create complex informational highways for precision transportation. The proposed evolutionary explanation is simply "co-option." A nebulous term which basically amounts to, "We don't know how it evolved, but it must have evolved from some other thing that was similar in the past." No observational data supports evolutionary co-option. It's absurd to believe any part of this was built by blind chance. Everything in the cell points to Intelligent Design.
0:59

This is a Kinesin Molecule. These little molecular machines are commonly referred to as the "workhorse" of the cell, hauling important cargo like organelles, proteins and other cellular structures to their proper location within the cell. Kinesins are very clear & undeniable evidence of the intelligent design in Life. Kinesins are complex molecular machines, made up of 4 total proteins, each between 500-1,300 amino acids in length. If these aa sequences are not perfectly aligned from the beginning, Kinesin never forms, and cellular life would be unable to survive. Here is how they work: When a new protein, organelle, or other cellular structure is created in the Cytosol of the cell, they are constructed with built-in "binding tags," which are like shipping labels that bind to other protein molecules called Adaptor or Scaffold Proteins. These Adaptor/Scaffold Proteins then attach to the Kinesin's tail, which activates them, and then the Kinesin is guided along the microtubule track to its to its final destination. Kinesin walk on self-assembling tracks of other proteins, called microtubules, moving cargo from the inner area of the cell where they are constructed to the outer edges where they function. This is a complex & sophisticated interdependent network of molecular machines, all relying on one another to function properly for the health of the cell. This Intracellular Transportation system MUST be fully functional from the beginning - with all these working parts, or all of it fails, and the cell dies. Without this entire functioning system, Life could not exist. And the Kinesin is the centerpiece to all of it. Experiments have shown that disrupting Kinesin activity has catastrophic consequences. This type of nano-precision is an obvious example of designed engineering. Blind, unguided evolutionary processes cannot plan ahead and create complex informational highways for precision transportation. The proposed evolutionary explanation is simply "co-option." A nebulous term which basically amounts to, "We don't know how it evolved, but it must have evolved from some other thing that was similar in the past." No observational data supports evolutionary co-option. It's absurd to believe any part of this was built by blind chance. Everything in the cell points to Intelligent Design.

Divinely Designed

15,877 次观看 • 6 个月前

"Frankenstein Proteins" The technology underpinning every mRNA 'vaccine' is creating strange "Frankenstein proteins" in the body and "no one knows what those proteins are doing". Pseudouridine was given a Nobel Prize before peer reviewed research from Cambridge found strange proteins circulating in the body of the vaccinated. Dr Ryan Cole discusses with Dr Kelly Victory: "This means is you're also coding for Frankenstein proteins, which may be functional, which may be triggering autoimmune reactions." "You're making proteins in addition to, you know the supposed spike protein, you're making unintended but potentially consequential proteins, that can cause the immune system also to go haywire." "So this was found out a couple years into the rollout of the shots and these very esteemed researchers said 'Houston we have a problem'. " Yet Paul Offit and the AAP wants this injected into healthy 2 year olds and children. Who has the moral high ground here?
2:34

"Frankenstein Proteins" The technology underpinning every mRNA 'vaccine' is creating strange "Frankenstein proteins" in the body and "no one knows what those proteins are doing". Pseudouridine was given a Nobel Prize before peer reviewed research from Cambridge found strange proteins circulating in the body of the vaccinated. Dr Ryan Cole discusses with Dr Kelly Victory: "This means is you're also coding for Frankenstein proteins, which may be functional, which may be triggering autoimmune reactions." "You're making proteins in addition to, you know the supposed spike protein, you're making unintended but potentially consequential proteins, that can cause the immune system also to go haywire." "So this was found out a couple years into the rollout of the shots and these very esteemed researchers said 'Houston we have a problem'. " Yet Paul Offit and the AAP wants this injected into healthy 2 year olds and children. Who has the moral high ground here?

Humanspective

15,413 次观看 • 10 个月前

NVIDIA CEO Jensen Huang just gave us a glimpse into the future of AI, and it's far bigger than text and images. He asked: "If you can understand worlds, is it possible that you understand proteins and chemicals that have structure?” This is the quiet revolution happening in AI right now. We're moving from an AI that understands human language to an AI that understands the language of nature itself. The "letters" are atoms. The "words" are molecules. The "sentences" are the complex structures of life, networks, and reality. The same foundational models that generate video are now being used to: *Decode proteins to fight disease *Design new materials at the atomic level *Simulate complex systems in quantum computing These were once the domain of supercomputers and Nobel laureates. Now, they're becoming solvable problems for a new generation of startups. AI is transitioning from a tool for communication to a tool for creation and discovery in the physical world. This is where the next wave of generational companies will be built. The "hard-to-solve" problems are now within reach.
2:14

NVIDIA CEO Jensen Huang just gave us a glimpse into the future of AI, and it's far bigger than text and images. He asked: "If you can understand worlds, is it possible that you understand proteins and chemicals that have structure?” This is the quiet revolution happening in AI right now. We're moving from an AI that understands human language to an AI that understands the language of nature itself. The "letters" are atoms. The "words" are molecules. The "sentences" are the complex structures of life, networks, and reality. The same foundational models that generate video are now being used to: *Decode proteins to fight disease *Design new materials at the atomic level *Simulate complex systems in quantum computing These were once the domain of supercomputers and Nobel laureates. Now, they're becoming solvable problems for a new generation of startups. AI is transitioning from a tool for communication to a tool for creation and discovery in the physical world. This is where the next wave of generational companies will be built. The "hard-to-solve" problems are now within reach.

Konstantine Buhler

13,014 次观看 • 9 个月前

#NewPaper The first microscope, invented in the 16th century, was designed to unlock the secrets of the microscopic world. Today, as many fields become increasingly data-driven, there is a pressing need for new types of microscopes---tools that help us zoom in, explore, and understand complex data. We call these tools "algorithmic microscopes." Introducing the Vendiscope: The first algorithmic microscope for data collections. 🔬 The Vendiscope maximizes the probability-weighted Vendi Score of a dataset to assign a weight to each element in the collection. This weight represents a data point's contribution to the overall diversity of the collection. These weights enable high-resolution data analysis at scale. We use them to zoom in on datasets across three domains: biology, materials science, & AI. 🧬 Biology: We used the Vendiscope on the protein universe, which contains nearly 250 million proteins. We found that nearly 200 million of the proteins are near-duplicates of each other and that AlphaFold fails on proteins that contribute most to the diversity of the protein universe. (See GIF below). 🪜 Materials Science: We used the Vendiscope on the Materials Project database, which contains 170K materials as of today. We found that 85% of crystals with formation energy data are near-duplicates of each other and that ML models for materials property prediction struggle with materials that contribute most to diversity. 🤖 Artificial Intelligence: We applied the Vendiscope to CIFAR-10, a benchmark dataset containing 50K images. We found duplicates. We applied the Vendiscope to analyze state-of-the-art generative models trained on this dataset. We found the best generative models memorize training data, as is known in the AI literature. However, we can do more with the Vendiscope and characterize the type of samples that get memorized. We found that data points contributing least to diversity are more prone to memorization by these generative models. 🧠 "Our findings demonstrate that the Vendiscope can serve as a powerful tool for data-driven science, providing a systematic and scalable way to identify duplicates and outliers, as well as pinpointing samples prone to memorization and those that models may struggle to predict---even before training." 💫 "The Vendiscope provides a unified framework for analyzing complex data at scale. Researchers, engineers, and data auditors can use the Vendiscope to audit datasets, identify potential biases, and refine data collection practices. For AI ethicists, the Vendiscope offers a critical lens to understand how models interact with data, particularly in the context of bias, memorization, and data fairness, enabling better mitigation strategies to prevent undesirable outcomes in AI deployment. For scientists, the Vendiscope represents a new companion in the discovery process." #VendiScoring #AlgorithmicMicroscopy Link to paper: Authors: Amey Pasarkar (Amey Pasarkar) and Adji Bousso Dieng (@adjiboussodieng)
0:30

#NewPaper The first microscope, invented in the 16th century, was designed to unlock the secrets of the microscopic world. Today, as many fields become increasingly data-driven, there is a pressing need for new types of microscopes---tools that help us zoom in, explore, and understand complex data. We call these tools "algorithmic microscopes." Introducing the Vendiscope: The first algorithmic microscope for data collections. 🔬 The Vendiscope maximizes the probability-weighted Vendi Score of a dataset to assign a weight to each element in the collection. This weight represents a data point's contribution to the overall diversity of the collection. These weights enable high-resolution data analysis at scale. We use them to zoom in on datasets across three domains: biology, materials science, & AI. 🧬 Biology: We used the Vendiscope on the protein universe, which contains nearly 250 million proteins. We found that nearly 200 million of the proteins are near-duplicates of each other and that AlphaFold fails on proteins that contribute most to the diversity of the protein universe. (See GIF below). 🪜 Materials Science: We used the Vendiscope on the Materials Project database, which contains 170K materials as of today. We found that 85% of crystals with formation energy data are near-duplicates of each other and that ML models for materials property prediction struggle with materials that contribute most to diversity. 🤖 Artificial Intelligence: We applied the Vendiscope to CIFAR-10, a benchmark dataset containing 50K images. We found duplicates. We applied the Vendiscope to analyze state-of-the-art generative models trained on this dataset. We found the best generative models memorize training data, as is known in the AI literature. However, we can do more with the Vendiscope and characterize the type of samples that get memorized. We found that data points contributing least to diversity are more prone to memorization by these generative models. 🧠 "Our findings demonstrate that the Vendiscope can serve as a powerful tool for data-driven science, providing a systematic and scalable way to identify duplicates and outliers, as well as pinpointing samples prone to memorization and those that models may struggle to predict---even before training." 💫 "The Vendiscope provides a unified framework for analyzing complex data at scale. Researchers, engineers, and data auditors can use the Vendiscope to audit datasets, identify potential biases, and refine data collection practices. For AI ethicists, the Vendiscope offers a critical lens to understand how models interact with data, particularly in the context of bias, memorization, and data fairness, enabling better mitigation strategies to prevent undesirable outcomes in AI deployment. For scientists, the Vendiscope represents a new companion in the discovery process." #VendiScoring #AlgorithmicMicroscopy Link to paper: Authors: Amey Pasarkar (Amey Pasarkar) and Adji Bousso Dieng (@adjiboussodieng)

Vertaix® (AI & Science)

34,762 次观看 • 1 年前

"The industry has been plagued with the problem, that these formulations are toxic". NEW World Premiere. "Inside mRNA Vaccines". Robert Malone MD addresses the technology underpinning every single "safe and effective" mRNA injection. Pseudouridine. It was given a Nobel Prize, before a peer reviewed paper from Cambridge found strange proteins in the blood of vaccinated people and "no one knows what those proteins are doing". Professor Robert Clancy said of the same Cambridge research in another separate interview: "the Nobel Prize in 2023 was given to two people for putting pseudouridine in a messenger RNA, to make it work better" "Within three months, a group in Cambridge found that 20% of readouts, and about 10% of people, had strange proteins circulating in their bodies, some of which have the capacity to form amyloid, which can cause dementia [and] they found this within weeks and months of people being vaccinated" "They worked out that the mechanism was because the pseudouridine [was producing]—instead of a spike protein—something completely strange and different" "No one knows what those proteins are doing"
2:39

"The industry has been plagued with the problem, that these formulations are toxic". NEW World Premiere. "Inside mRNA Vaccines". Robert Malone MD addresses the technology underpinning every single "safe and effective" mRNA injection. Pseudouridine. It was given a Nobel Prize, before a peer reviewed paper from Cambridge found strange proteins in the blood of vaccinated people and "no one knows what those proteins are doing". Professor Robert Clancy said of the same Cambridge research in another separate interview: "the Nobel Prize in 2023 was given to two people for putting pseudouridine in a messenger RNA, to make it work better" "Within three months, a group in Cambridge found that 20% of readouts, and about 10% of people, had strange proteins circulating in their bodies, some of which have the capacity to form amyloid, which can cause dementia [and] they found this within weeks and months of people being vaccinated" "They worked out that the mechanism was because the pseudouridine [was producing]—instead of a spike protein—something completely strange and different" "No one knows what those proteins are doing"

Humanspective

10,202 次观看 • 11 个月前

This is concerning on so many levels: "No one knows what those proteins are doing" Professor Robert Clancy: "the Nobel Prize in 2023 was given to two people for putting pseudouridine in a messenger RNA [but the] pseudouridine [was producing]—instead of a spike protein—something completely strange and different" That Nobel Prize in 2023 meets a peer reviewed study from Cambridge, which might have outlined a mechanism behind why embalmers are seeing the "strange rubbery clots" in the deceased. AND, the Yale evidence of persistent spike production of 709 x days, however that's happening, gives a cautionary but plausible amyloidogenic mechanism for abnormal proteins to be produced both acutely and for extended periods. Professor Robert Clancy: "the Nobel Prize in 2023 was given to two people for putting pseudouridine in a messenger RNA, to make it work better" "Within three months, a group in Cambridge found that 20% of readouts, and about 10% of people, had strange proteins circulating in their bodies, some of which have the capacity to form amyloid, which can cause dementia [and] they found this within weeks and months of people being vaccinated" "They worked out that the mechanism was because the pseudouridine [was producing]—instead of a spike protein—something completely strange and different"
3:04

This is concerning on so many levels: "No one knows what those proteins are doing" Professor Robert Clancy: "the Nobel Prize in 2023 was given to two people for putting pseudouridine in a messenger RNA [but the] pseudouridine [was producing]—instead of a spike protein—something completely strange and different" That Nobel Prize in 2023 meets a peer reviewed study from Cambridge, which might have outlined a mechanism behind why embalmers are seeing the "strange rubbery clots" in the deceased. AND, the Yale evidence of persistent spike production of 709 x days, however that's happening, gives a cautionary but plausible amyloidogenic mechanism for abnormal proteins to be produced both acutely and for extended periods. Professor Robert Clancy: "the Nobel Prize in 2023 was given to two people for putting pseudouridine in a messenger RNA, to make it work better" "Within three months, a group in Cambridge found that 20% of readouts, and about 10% of people, had strange proteins circulating in their bodies, some of which have the capacity to form amyloid, which can cause dementia [and] they found this within weeks and months of people being vaccinated" "They worked out that the mechanism was because the pseudouridine [was producing]—instead of a spike protein—something completely strange and different"

Humanspective

202,591 次观看 • 1 年前

Creator of C#, Anders Hejlsberg(Anders Hejlsberg), on the design goals that shaped the language and why standardisation was a goal from the beginning: “The overarching thing was this power and productivity of C++ with the ease of use of Visual Basic. We knew we wanted to build an object oriented language. We wanted managed code or byte code so we could target different runtime environments. We wanted garbage collection and exception handling, but also things like a unified object system where, and that's true in C#, anything can be assigned to an object. If it's a value type, we box it. And it's a self-describing object. So, reflection: you can ask an object, ‘what are you’? And you can get all of the facts about it at runtime, and you can dynamically manipulate it in ways that just don't exist in a lot of other environments. We wanted a language that made this new model of properties, methods and events first class because that was how components were built as opposed to just sort of functions and procedures and even objects. And we wanted to create a language that was standardised. We wanted to give this language to a standardisation committee and try to level the playing field there. And all of those things were sort of like what was rolled up in C#”
1:43

Creator of C#, Anders Hejlsberg(Anders Hejlsberg), on the design goals that shaped the language and why standardisation was a goal from the beginning: “The overarching thing was this power and productivity of C++ with the ease of use of Visual Basic. We knew we wanted to build an object oriented language. We wanted managed code or byte code so we could target different runtime environments. We wanted garbage collection and exception handling, but also things like a unified object system where, and that's true in C#, anything can be assigned to an object. If it's a value type, we box it. And it's a self-describing object. So, reflection: you can ask an object, ‘what are you’? And you can get all of the facts about it at runtime, and you can dynamically manipulate it in ways that just don't exist in a lot of other environments. We wanted a language that made this new model of properties, methods and events first class because that was how components were built as opposed to just sort of functions and procedures and even objects. And we wanted to create a language that was standardised. We wanted to give this language to a standardisation committee and try to level the playing field there. And all of those things were sort of like what was rolled up in C#”

The Pragmatic Engineer

18,332 次观看 • 1 个月前

“You can look at sort of broad allergic reactions that take place across an entire society that are linked to the vaccine schedule.” RFK Jr just explained that studies show certain vaccine ingredients have triggered spikes in allergies. “I’ll say one thing about the residual food proteins in vaccines because the science suggests that aluminum alone will not cause allergies… but when it’s combined with a protein, if it’s a latex protein or a dairy protein or a peanut protein, that’s when you get this heightened immune response.” “In the 1990s, there were a lot of anaphylaxis cases suddenly exploding in Japan.” “And they traced it to gelatin in the live virus vaccines and the MMR vaccines and some of the other vaccines they had over there.” “And by 2000, they had removed it all and the anaphylaxis dropped dramatically.” “There's no question about this, there was all kinds of studies done on the Japanese example.”
1:29

“You can look at sort of broad allergic reactions that take place across an entire society that are linked to the vaccine schedule.” RFK Jr just explained that studies show certain vaccine ingredients have triggered spikes in allergies. “I’ll say one thing about the residual food proteins in vaccines because the science suggests that aluminum alone will not cause allergies… but when it’s combined with a protein, if it’s a latex protein or a dairy protein or a peanut protein, that’s when you get this heightened immune response.” “In the 1990s, there were a lot of anaphylaxis cases suddenly exploding in Japan.” “And they traced it to gelatin in the live virus vaccines and the MMR vaccines and some of the other vaccines they had over there.” “And by 2000, they had removed it all and the anaphylaxis dropped dramatically.” “There's no question about this, there was all kinds of studies done on the Japanese example.”

End Tribalism in Politics

21,011 次观看 • 8 个月前

Most people don’t truly understand how mRNA vaccines work. Unlike traditional vaccines, where a factory produces the antigen and injects it into the body, mRNA vaccines turn YOUR OWN CELLS into the factory. Here’s how it works: Inside every one of your cells, there are ribosomes—tiny protein-making machines. Normally, these ribosomes get instructions from your cell’s nucleus (the brain of the cell) to produce proteins that build muscle, fight infections, and keep your body functioning. mRNA vaccines hijack this natural process by delivering a blueprint that instructs your ribosomes to produce a specific protein—like the spike protein of a virus. Your immune system then recognizes this protein as foreign, triggering a defense response and preparing your body to fight off future infections. Why does this matter? 1️⃣ Faster production – No need for external manufacturing of viral proteins, cutting vaccine development time. 2️⃣ Adaptability – The technology can be rapidly adjusted for new viruses and mutations. 3️⃣ No live virus – Unlike traditional vaccines, mRNA vaccines don’t use weakened or dead viruses, reducing risk. But here’s the big question: Are we playing with fire, or is this the future of medicine? We’re bypassing nature’s traditional immune response by directly programming our cells to make viral proteins. Dr. Mink Chawla and I break it all down in this episode. WATCH HERE:
0:48

Most people don’t truly understand how mRNA vaccines work. Unlike traditional vaccines, where a factory produces the antigen and injects it into the body, mRNA vaccines turn YOUR OWN CELLS into the factory. Here’s how it works: Inside every one of your cells, there are ribosomes—tiny protein-making machines. Normally, these ribosomes get instructions from your cell’s nucleus (the brain of the cell) to produce proteins that build muscle, fight infections, and keep your body functioning. mRNA vaccines hijack this natural process by delivering a blueprint that instructs your ribosomes to produce a specific protein—like the spike protein of a virus. Your immune system then recognizes this protein as foreign, triggering a defense response and preparing your body to fight off future infections. Why does this matter? 1️⃣ Faster production – No need for external manufacturing of viral proteins, cutting vaccine development time. 2️⃣ Adaptability – The technology can be rapidly adjusted for new viruses and mutations. 3️⃣ No live virus – Unlike traditional vaccines, mRNA vaccines don’t use weakened or dead viruses, reducing risk. But here’s the big question: Are we playing with fire, or is this the future of medicine? We’re bypassing nature’s traditional immune response by directly programming our cells to make viral proteins. Dr. Mink Chawla and I break it all down in this episode. WATCH HERE:

Gary Brecka

51,737 次观看 • 1 年前

I do not know who the guy is on the podcast with Raj Shamani, but he is absolutely wrong. There seems to be a section of "health influencers" who fearmonger the public on "dangers of whey protein or protein supplementation." Ammonia production is not a side effect of whey protein metabolism, but is a normal metabolic product of any protein metabolism. Ammonia is natural, generated as a by-product of protein ingestion through the breakdown of amino acids. Of the amino acids, glutamate is the one that has maximal free ammonia generation. In normal healthy persons, excessive ammonia generation is handled by the body and it does not affect brain function. This is done via the "urea cycle" in the liver: In patients with liver disease such as acute liver failure or chronic liver failure, the excess ammonia cannot be cleared out by the weak/failing liver or utilized in the muscles (because of muscle loss in liver patients) and affects brain functioning, leading to a condition called hepatic encephalopathy. This does not happen if you are healthy and taking additional protein. In fact, animal meats are more ammonia generating than plant-based or dairy-based protein and in those chronic liver failure patients with recurrent or persistent ammonia related brain dysfunction, the dietary advise is to limit animal meats and include more or switch to dairy+plant-based protein to keep ammonia generation low. Whey protein and scoops of additional whey protein to target protein requirement is perfectly safe and does not affect brain function or make the person slow like what is discussed in this video. Even advanced cirrhosis patients are supplemented with whey based protein formulations to target additional protein requirements and improve quality of life and immune functions Eg: and I hope we develop a law to deport brain dead misinformation peddling sub-standard "health influencers," like this guy in suit.
0:39

I do not know who the guy is on the podcast with Raj Shamani, but he is absolutely wrong. There seems to be a section of "health influencers" who fearmonger the public on "dangers of whey protein or protein supplementation." Ammonia production is not a side effect of whey protein metabolism, but is a normal metabolic product of any protein metabolism. Ammonia is natural, generated as a by-product of protein ingestion through the breakdown of amino acids. Of the amino acids, glutamate is the one that has maximal free ammonia generation. In normal healthy persons, excessive ammonia generation is handled by the body and it does not affect brain function. This is done via the "urea cycle" in the liver: In patients with liver disease such as acute liver failure or chronic liver failure, the excess ammonia cannot be cleared out by the weak/failing liver or utilized in the muscles (because of muscle loss in liver patients) and affects brain functioning, leading to a condition called hepatic encephalopathy. This does not happen if you are healthy and taking additional protein. In fact, animal meats are more ammonia generating than plant-based or dairy-based protein and in those chronic liver failure patients with recurrent or persistent ammonia related brain dysfunction, the dietary advise is to limit animal meats and include more or switch to dairy+plant-based protein to keep ammonia generation low. Whey protein and scoops of additional whey protein to target protein requirement is perfectly safe and does not affect brain function or make the person slow like what is discussed in this video. Even advanced cirrhosis patients are supplemented with whey based protein formulations to target additional protein requirements and improve quality of life and immune functions Eg: and I hope we develop a law to deport brain dead misinformation peddling sub-standard "health influencers," like this guy in suit.

TheLiverDoc™

241,731 次观看 • 2 年前

It’s embarrassing to watch the TGA tie itself up in knots and contradict itself over the safety of the vaccine. The mRNA vaccine is designed to attack your own cells because the antigen sits on the cell membrane. The T-cell which responds to the vaccine antigen can’t separate your cell from the spike protein. It kills both and the TGA has already admitted as much in the past conceding myocarditis is an autoimmune response. The spike proteins are not rapidly degraded as numerous studies have shown they last in the body for up to 60 days. But more importantly the mRNA is designed to last much longer and produce more proteins. This means the body produces a much larger concentration of the toxic spike protein than what the virus would have delivered. And I quote from one study: “Later studies documented similar effects for 5-methylcytidine and 2-thiouridine and observed that modified mRNAs produced 10- to 100-fold more protein compared with unmodified mRNAs. Recently, N1-methylpseudouridine (m1Ψ), the modification used in the current mRNA SARS-CoV-2 vaccines, was found to possess superior characteristics to Ψ; m1Ψ elicited less immunogenicity and increased protein production by more than an order of magnitude relative to Ψ.” And another on the Poly-A tail increases the duration. “Whether for the mRNA vaccine from Pfizer/BioNtech® laboratories or that of Moderna®, the two mRNA sequences end in a Poly(A) tail. The purpose of this addition is to increase the stability of the mRNA in biological medium and also to allow the recruitment of the ribosome, in order to initiate an efficient translation. After translation, the mRNA can be reused several times, but when this happens, it also loses part of the Adenines of its Poly(A) tail, as enzymatic degradation begins there, which only ensures a transient protection against this degradation. When this tail is too degraded, the mRNA is no longer functional and is destroyed. The poly(A) tail stabilizes mRNA and boosts protein translation, and the length of the poly(A) tail is proportional to translation efficiency. It is a critical factor in determining the longevity of mRNA molecules.” Long story short - the TGA continues to lie. Quotes from: #auspol
2:19

It’s embarrassing to watch the TGA tie itself up in knots and contradict itself over the safety of the vaccine. The mRNA vaccine is designed to attack your own cells because the antigen sits on the cell membrane. The T-cell which responds to the vaccine antigen can’t separate your cell from the spike protein. It kills both and the TGA has already admitted as much in the past conceding myocarditis is an autoimmune response. The spike proteins are not rapidly degraded as numerous studies have shown they last in the body for up to 60 days. But more importantly the mRNA is designed to last much longer and produce more proteins. This means the body produces a much larger concentration of the toxic spike protein than what the virus would have delivered. And I quote from one study: “Later studies documented similar effects for 5-methylcytidine and 2-thiouridine and observed that modified mRNAs produced 10- to 100-fold more protein compared with unmodified mRNAs. Recently, N1-methylpseudouridine (m1Ψ), the modification used in the current mRNA SARS-CoV-2 vaccines, was found to possess superior characteristics to Ψ; m1Ψ elicited less immunogenicity and increased protein production by more than an order of magnitude relative to Ψ.” And another on the Poly-A tail increases the duration. “Whether for the mRNA vaccine from Pfizer/BioNtech® laboratories or that of Moderna®, the two mRNA sequences end in a Poly(A) tail. The purpose of this addition is to increase the stability of the mRNA in biological medium and also to allow the recruitment of the ribosome, in order to initiate an efficient translation. After translation, the mRNA can be reused several times, but when this happens, it also loses part of the Adenines of its Poly(A) tail, as enzymatic degradation begins there, which only ensures a transient protection against this degradation. When this tail is too degraded, the mRNA is no longer functional and is destroyed. The poly(A) tail stabilizes mRNA and boosts protein translation, and the length of the poly(A) tail is proportional to translation efficiency. It is a critical factor in determining the longevity of mRNA molecules.” Long story short - the TGA continues to lie. Quotes from: #auspol

Gerard Rennick

62,522 次观看 • 1 年前

We are excited to share #PDF2Audio, an open-source alternative to the #podcast feature of #NotebookLM with flexibility & tailored outputs that you can precisely control in the app: You can make a podcast, lecture, discussions, short/long form summaries & more, including the use of the amazing🍓o1 model (Sam Altman OpenAI: with stunning results!). Code & HF Space: You can find #PDF2Audio on GitHub for local use or try the Hugging Face space, all featuring Gradio. Link to the repo & HF space in the reply. Thank you @knowsuchagencyfor the great work on #promptic and #pdf2podcast, as well as LiteLLM (YC W23), & AK for helping us with the Hugging Face spaces version. We hope that this tool is useful for the community. Background: Developing audio podcasts, lectures, & summaries from complex documents & data has become an exciting trend with impacts from research to education to business. Our open-source #PDF2Audio tool that allows users to utilize various models such as #o1 or local/open-source models, to develop deep-dives into technical content. Example application - material design analysis: As an example to show what the system can do, check the video for a detailed 13-minute analysis of one of the designs created by #SciAgents merging silk & dandelion pigments, created using 🍓o1. The conversation describes the new material, an integration of silk proteins & luteolin/dandelion pigments to create a new biomaterial. Silk, a natural #nanostructured protein-based fiber known for its strength & flexibility, is combined with dandelion pigments like luteolin, which offer unique optical properties. By merging these components at the nanoscale level, the resulting material displays structural coloration—vibrant, tunable colors created by the material's structure rather than synthetic dyes, and leverages silk's hierarchical organization as a scaffold for the pigments, ensuring uniform distribution and non-covalent bonding at the molecular level. Key technical features include: ➡️Low-temperature processing to maintain the integrity of both silk and pigments while reducing energy consumption by 30%. ➡️Enhanced mechanical properties, with tensile strength up to 1.5 gigapascals. ➡️Potential self-healing capabilities and environmental responsiveness, allowing the material to repair minor damage and change color based on environmental conditions. ➡️UV protection and antimicrobial properties, which make this material ideal for smart textiles, eco-friendly coatings, and medical applications. This development opens new doors for sustainable materials, offering an eco-friendly alternative to synthetic fibers with applications in various industries, from fashion to healthcare.
13:05

We are excited to share #PDF2Audio, an open-source alternative to the #podcast feature of #NotebookLM with flexibility & tailored outputs that you can precisely control in the app: You can make a podcast, lecture, discussions, short/long form summaries & more, including the use of the amazing🍓o1 model (Sam Altman OpenAI: with stunning results!). Code & HF Space: You can find #PDF2Audio on GitHub for local use or try the Hugging Face space, all featuring Gradio. Link to the repo & HF space in the reply. Thank you @knowsuchagencyfor the great work on #promptic and #pdf2podcast, as well as LiteLLM (YC W23), & AK for helping us with the Hugging Face spaces version. We hope that this tool is useful for the community. Background: Developing audio podcasts, lectures, & summaries from complex documents & data has become an exciting trend with impacts from research to education to business. Our open-source #PDF2Audio tool that allows users to utilize various models such as #o1 or local/open-source models, to develop deep-dives into technical content. Example application - material design analysis: As an example to show what the system can do, check the video for a detailed 13-minute analysis of one of the designs created by #SciAgents merging silk & dandelion pigments, created using 🍓o1. The conversation describes the new material, an integration of silk proteins & luteolin/dandelion pigments to create a new biomaterial. Silk, a natural #nanostructured protein-based fiber known for its strength & flexibility, is combined with dandelion pigments like luteolin, which offer unique optical properties. By merging these components at the nanoscale level, the resulting material displays structural coloration—vibrant, tunable colors created by the material's structure rather than synthetic dyes, and leverages silk's hierarchical organization as a scaffold for the pigments, ensuring uniform distribution and non-covalent bonding at the molecular level. Key technical features include: ➡️Low-temperature processing to maintain the integrity of both silk and pigments while reducing energy consumption by 30%. ➡️Enhanced mechanical properties, with tensile strength up to 1.5 gigapascals. ➡️Potential self-healing capabilities and environmental responsiveness, allowing the material to repair minor damage and change color based on environmental conditions. ➡️UV protection and antimicrobial properties, which make this material ideal for smart textiles, eco-friendly coatings, and medical applications. This development opens new doors for sustainable materials, offering an eco-friendly alternative to synthetic fibers with applications in various industries, from fashion to healthcare.

Markus J. Buehler

208,353 次观看 • 1 年前