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Today we introduced AlphaGenome, a new tool that can more comprehensively predict the impact of single variants or mutations in DNA 🧬 How, you ask? 🤔 tldr; Our AlphaGenome model takes a long DNA sequence as input, processes that data, and predicts thousands of molecular properties by characterizing its... show more

Google AI

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83,048 views • 1 year ago •via X (Twitter)

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🧬 We have many foundation models or language models for DNAs, but can we control them? We introduce Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RL — a reinforcement learning framework for controllable cis-regulatory sequence generation. Paper: Code: 🔬What’s the challenge? Designing regulatory DNA that is both highly expressive in target cell types and inactive in others is essential for synthetic biology, gene therapy, and precision medicine. Yet, controlling these trade-offs is challenging due to sparse, sequence-level rewards and biological constraints. 🔥Why Ctrl-DNA? Ctrl-DNA fine-tunes pre-trained DNA language models using a value model free, Lagrangian-guided RL framework, enabling flexible and customizable constraint optimization. Users can define application-specific thresholds across cell types, balancing expression strength with specificity. ✅ Maximize target-cell expression ✅ Constrain off-target activity under user-defined thresholds ✅ Preserve cell-type-specific TF motif structure Benchmarked on human enhancer and promoter datasets, Ctrl-DNA consistently outperforms prior methods, achieving stronger specificity, higher fitness, and more biologically grounded sequence generation — all with direct control over regulatory trade-offs. Shoutout to the PhD students Xingyu Chen (Xingyu Chen ) and Rex Ma (Rex Ma) for their amazing work leading this project!

🧬 We have many foundation models or language models for DNAs, but can we control them? We introduce Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RL — a reinforcement learning framework for controllable cis-regulatory sequence generation. Paper: Code: 🔬What’s the challenge? Designing regulatory DNA that is both highly expressive in target cell types and inactive in others is essential for synthetic biology, gene therapy, and precision medicine. Yet, controlling these trade-offs is challenging due to sparse, sequence-level rewards and biological constraints. 🔥Why Ctrl-DNA? Ctrl-DNA fine-tunes pre-trained DNA language models using a value model free, Lagrangian-guided RL framework, enabling flexible and customizable constraint optimization. Users can define application-specific thresholds across cell types, balancing expression strength with specificity. ✅ Maximize target-cell expression ✅ Constrain off-target activity under user-defined thresholds ✅ Preserve cell-type-specific TF motif structure Benchmarked on human enhancer and promoter datasets, Ctrl-DNA consistently outperforms prior methods, achieving stronger specificity, higher fitness, and more biologically grounded sequence generation — all with direct control over regulatory trade-offs. Shoutout to the PhD students Xingyu Chen (Xingyu Chen ) and Rex Ma (Rex Ma) for their amazing work leading this project!

Bo Wang

30,719 views • 1 year ago

How do you architect one brand for multiple regulated businesses? For Ceviant, we built a universe of expression around the original logo's DNA. Each sub-brand gets a unique polygon that defines its patterns, layouts, and visual world. 🧵↓

FourthCanvas

27,813 views • 7 months ago

This week, we shipped new features to give you more control over how and where you experience YouTube: 🥽 You can now watch YouTube videos on Samsung Electronics Galaxy XR, the first Android XR headset. In your own YouTube theater, you can explore the world’s largest library of 180 and 360-degree VR content. Read more: ⏰ With our new Shorts feed timer, you can set a daily limit for how long you scroll through Shorts. This tool comes in addition to existing wellbeing features, like take-a-break and bedtime reminders. Learn more:

This week, we shipped new features to give you more control over how and where you experience YouTube: 🥽 You can now watch YouTube videos on Samsung Electronics Galaxy XR, the first Android XR headset. In your own YouTube theater, you can explore the world’s largest library of 180 and 360-degree VR content. Read more: ⏰ With our new Shorts feed timer, you can set a daily limit for how long you scroll through Shorts. This tool comes in addition to existing wellbeing features, like take-a-break and bedtime reminders. Learn more:

Neal Mohan

327,433 views • 8 months ago

The final Epoch is now complete. DNA becomes fully deflationary. 3 years ago, we bet on a revenue-share model before it was the meta. While the market was chasing high inflation tokens, we were building a sustainable system for the first truly on-chain DAO on Multiversᕽ. It was an experiment, and it is now battle-tested. The proof is on-chain. Over the last 4 epochs, the DAO generated enough revenue to buy back over 6m $DNA from the total supply. Even with EGLD dropping ~90% since our token fair-launch (with no raise, pre-mine, allocations, or hidden unlocks) $DNA sits at roughly the same USD price today as it did on Day 1. The DNA/EGLD pair has outperformed the market and remained healthy, proving the model works even in the toughest conditions. Now, the dynamic flips. Emissions have officially ended. We are entering a full deflationary cycle. No more DNA will be printed, but the DAO will keep buying. We expect the value of DNA to reflect this scarcity, while the power of your Subject X NFTs remains the key to accessing that value. What’s next? We switch our focus fully to strengthening the MultiversX ecosystem. We are here to build tools, products, and open-source tech that grow the chain. When EGLD grows, our products grow. When our products grow, the DAO earns more. When the DAO earns more, $DNA gets stronger. Thank you to everyone who made this journey possible. History is written. Now we continue building.

The final Epoch is now complete. DNA becomes fully deflationary. 3 years ago, we bet on a revenue-share model before it was the meta. While the market was chasing high inflation tokens, we were building a sustainable system for the first truly on-chain DAO on Multiversᕽ. It was an experiment, and it is now battle-tested. The proof is on-chain. Over the last 4 epochs, the DAO generated enough revenue to buy back over 6m $DNA from the total supply. Even with EGLD dropping ~90% since our token fair-launch (with no raise, pre-mine, allocations, or hidden unlocks) $DNA sits at roughly the same USD price today as it did on Day 1. The DNA/EGLD pair has outperformed the market and remained healthy, proving the model works even in the toughest conditions. Now, the dynamic flips. Emissions have officially ended. We are entering a full deflationary cycle. No more DNA will be printed, but the DAO will keep buying. We expect the value of DNA to reflect this scarcity, while the power of your Subject X NFTs remains the key to accessing that value. What’s next? We switch our focus fully to strengthening the MultiversX ecosystem. We are here to build tools, products, and open-source tech that grow the chain. When EGLD grows, our products grow. When our products grow, the DAO earns more. When the DAO earns more, $DNA gets stronger. Thank you to everyone who made this journey possible. History is written. Now we continue building.

Project X 🧬

11,275 views • 6 months ago

We are excited to introduce Stable Fast 3D, Stability AI’s latest breakthrough in 3D asset generation technology. This innovative model transforms a single input image into a detailed 3D asset in just 0.5 seconds, setting a new standard for speed and quality in the field of 3D reconstruction! Alongside this release, we’ve also published a technical report that highlights how we achieve fast inference speeds with reduced baked illumination and material parameters. 👾You can learn more and access the report here:

We are excited to introduce Stable Fast 3D, Stability AI’s latest breakthrough in 3D asset generation technology. This innovative model transforms a single input image into a detailed 3D asset in just 0.5 seconds, setting a new standard for speed and quality in the field of 3D reconstruction! Alongside this release, we’ve also published a technical report that highlights how we achieve fast inference speeds with reduced baked illumination and material parameters. 👾You can learn more and access the report here:

Stability AI

438,350 views • 1 year ago

🚨 NASA JUST FOUND THE RAW INGREDIENTS OF DNA INSIDE A ROCK OLDER THAN EARTH ITSELF. Samples returned from the asteroid Bennu contain complex organic molecules including precursors to DNA and RNA, plus many of the amino acids used by all life on Earth. These molecules formed in the early solar system and survived for billions of years inside the asteroid. Earth didn’t have to invent the chemistry of life from nothing. It was delivered ready-made from space. Why this matters: • Bennu is a primitive asteroid that has remained largely unchanged since the birth of the solar system (~4.5 billion years ago) • The samples contain the molecular building blocks of DNA, RNA, and proteins the core components of life as we know it • These organics were preserved through the violent early days of the solar system and could have been delivered to Earth by asteroids and comets • This is some of the strongest direct evidence yet that life’s chemistry has cosmic origins The deeper implication: This doesn’t mean aliens or microbes came from space. It means the raw materials for life were already floating around the solar system long before Earth cooled enough to support life. Our planet likely received these ingredients from above rather than creating them all from scratch. If these building blocks were common in the early solar system, then the starting chemistry for life may have been widespread dramatically raising the chances that similar processes could have happened elsewhere. How does it change your perspective to know that the molecular ingredients for DNA were already present in space billions of years before the first living cell appeared on Earth? Follow for more discoveries about the origins of life and what we’re learning from asteroid samples.

🚨 NASA JUST FOUND THE RAW INGREDIENTS OF DNA INSIDE A ROCK OLDER THAN EARTH ITSELF. Samples returned from the asteroid Bennu contain complex organic molecules including precursors to DNA and RNA, plus many of the amino acids used by all life on Earth. These molecules formed in the early solar system and survived for billions of years inside the asteroid. Earth didn’t have to invent the chemistry of life from nothing. It was delivered ready-made from space. Why this matters: • Bennu is a primitive asteroid that has remained largely unchanged since the birth of the solar system (~4.5 billion years ago) • The samples contain the molecular building blocks of DNA, RNA, and proteins the core components of life as we know it • These organics were preserved through the violent early days of the solar system and could have been delivered to Earth by asteroids and comets • This is some of the strongest direct evidence yet that life’s chemistry has cosmic origins The deeper implication: This doesn’t mean aliens or microbes came from space. It means the raw materials for life were already floating around the solar system long before Earth cooled enough to support life. Our planet likely received these ingredients from above rather than creating them all from scratch. If these building blocks were common in the early solar system, then the starting chemistry for life may have been widespread dramatically raising the chances that similar processes could have happened elsewhere. How does it change your perspective to know that the molecular ingredients for DNA were already present in space billions of years before the first living cell appeared on Earth? Follow for more discoveries about the origins of life and what we’re learning from asteroid samples.

TheNewPhysics

87,603 views • 24 days ago

The Hidden Language of Diffusion Models paper page: tackle the challenge of understanding concept representations in text-to-image models by decomposing an input text prompt into a small set of interpretable elements. This is achieved by learning a pseudo-token that is a sparse weighted combination of tokens from the model's vocabulary, with the objective of reconstructing the images generated for the given concept. Applied over the state-of-the-art Stable Diffusion model, this decomposition reveals non-trivial and surprising structures in the representations of concepts. For example, we find that some concepts such as "a president" or "a composer" are dominated by specific instances (e.g., "Obama", "Biden") and their interpolations. Other concepts, such as "happiness" combine associated terms that can be concrete ("family", "laughter") or abstract ("friendship", "emotion"). In addition to peering into the inner workings of Stable Diffusion, our method also enables applications such as single-image decomposition to tokens, bias detection and mitigation, and semantic image manipulation

The Hidden Language of Diffusion Models paper page: tackle the challenge of understanding concept representations in text-to-image models by decomposing an input text prompt into a small set of interpretable elements. This is achieved by learning a pseudo-token that is a sparse weighted combination of tokens from the model's vocabulary, with the objective of reconstructing the images generated for the given concept. Applied over the state-of-the-art Stable Diffusion model, this decomposition reveals non-trivial and surprising structures in the representations of concepts. For example, we find that some concepts such as "a president" or "a composer" are dominated by specific instances (e.g., "Obama", "Biden") and their interpolations. Other concepts, such as "happiness" combine associated terms that can be concrete ("family", "laughter") or abstract ("friendship", "emotion"). In addition to peering into the inner workings of Stable Diffusion, our method also enables applications such as single-image decomposition to tokens, bias detection and mitigation, and semantic image manipulation

AK

41,746 views • 3 years ago

PSA: $NAM Airdrop 🪂 - only a few hours left ➡️Claim closes on: 12th of Jan 2024, at 9am ➡️ The _ONLY_ place to claim ➡️Allocations have been adjusted recently - check if you have claimed to see if your number went up! ➡️US is sadly geoblocked 🔸Eligibility and How to Claim reminder ➡️ $OSMO snapshot: mainnet block 12146298 ➡️ $ATOM snapshots: block 17660694 (the last blocks before 1st of November 2023). To be eligible you need to have at least $100 USD staked ➡️In $OSMO: 280 $OSMO ➡️In $ATOM: 12.786667 $ATOM Beyond staking every account gets an Activity Score. The TLDR; of this scoring method is that it measures the engagement of the account on a decentralized network. The specific framework used in the RPGF Drop is an adaptation from Trusta AI ' Media Score, and was first introduced by Celestia on the Genesis Drop. Based on the mechanism, the score can be a minimum of 1.5 and a maximum of 15. The Activity Score is a points system that takes into account activity such as transactions, ibc transfers, the value of transactions, months active, etc. (the scoring details are linked in the announcement). The maximum points you can get on the Activity Score is 15. To determine the tier, the amount staked at the time is multiplied by the Activity Score. Then all eligible accounts are ranked by highest value to lowest and grouped into tiers: top 10%, 50-90%, and 0-50% ➡️Source: MEDIA SCORE as the Infrastructure for On-chain User Value Assessment: 🔸How to claim $NAM airdrop ➡️Get Namada Wallet Extension ➡️Go to ➡️Connect Wallet $ATOM $OSMO $STARS ➡️Connect $NAM Extension ➡️CLAIM $NAM ➡️Repeat for any additional chains / wallets 🔸Looking for an easy and super clear "how to claim video"? @L1am_Crypto & Stakecito Labs to the rescue 🫡 🔸$NAM airdrop beraindex overview: 🔸Stake $ATOM with our sponsor, Enigma , and don't miss out on future Airdrops 🥩 $ATOM 🫡

PSA: $NAM Airdrop 🪂 - only a few hours left ➡️Claim closes on: 12th of Jan 2024, at 9am ➡️ The _ONLY_ place to claim ➡️Allocations have been adjusted recently - check if you have claimed to see if your number went up! ➡️US is sadly geoblocked 🔸Eligibility and How to Claim reminder ➡️ $OSMO snapshot: mainnet block 12146298 ➡️ $ATOM snapshots: block 17660694 (the last blocks before 1st of November 2023). To be eligible you need to have at least $100 USD staked ➡️In $OSMO: 280 $OSMO ➡️In $ATOM: 12.786667 $ATOM Beyond staking every account gets an Activity Score. The TLDR; of this scoring method is that it measures the engagement of the account on a decentralized network. The specific framework used in the RPGF Drop is an adaptation from Trusta AI ' Media Score, and was first introduced by Celestia on the Genesis Drop. Based on the mechanism, the score can be a minimum of 1.5 and a maximum of 15. The Activity Score is a points system that takes into account activity such as transactions, ibc transfers, the value of transactions, months active, etc. (the scoring details are linked in the announcement). The maximum points you can get on the Activity Score is 15. To determine the tier, the amount staked at the time is multiplied by the Activity Score. Then all eligible accounts are ranked by highest value to lowest and grouped into tiers: top 10%, 50-90%, and 0-50% ➡️Source: MEDIA SCORE as the Infrastructure for On-chain User Value Assessment: 🔸How to claim $NAM airdrop ➡️Get Namada Wallet Extension ➡️Go to ➡️Connect Wallet $ATOM $OSMO $STARS ➡️Connect $NAM Extension ➡️CLAIM $NAM ➡️Repeat for any additional chains / wallets 🔸Looking for an easy and super clear "how to claim video"? @L1am_Crypto & Stakecito Labs to the rescue 🫡 🔸$NAM airdrop beraindex overview: 🔸Stake $ATOM with our sponsor, Enigma , and don't miss out on future Airdrops 🥩 $ATOM 🫡

Grey Ledger

60,319 views • 2 years ago

Break-A-Scene: Extracting Multiple Concepts from a Single Image introduce the task of textual scene decomposition: given a single image of a scene that may contain several concepts, we aim to extract a distinct text token for each concept, enabling fine-grained control over the generated scenes. To this end, we propose augmenting the input image with masks that indicate the presence of target concepts. These masks can be provided by the user or generated automatically by a pre-trained segmentation model. We then present a novel two-phase customization process that optimizes a set of dedicated textual embeddings (handles), as well as the model weights, striking a delicate balance between accurately capturing the concepts and avoiding overfitting. We employ a masked diffusion loss to enable handles to generate their assigned concepts, complemented by a novel loss on cross-attention maps to prevent entanglement. We also introduce union-sampling, a training strategy aimed to improve the ability of combining multiple concepts in generated images. We use several automatic metrics to quantitatively compare our method against several baselines, and further affirm the results using a user study. Finally, we showcase several applications of our method paper page:

Break-A-Scene: Extracting Multiple Concepts from a Single Image introduce the task of textual scene decomposition: given a single image of a scene that may contain several concepts, we aim to extract a distinct text token for each concept, enabling fine-grained control over the generated scenes. To this end, we propose augmenting the input image with masks that indicate the presence of target concepts. These masks can be provided by the user or generated automatically by a pre-trained segmentation model. We then present a novel two-phase customization process that optimizes a set of dedicated textual embeddings (handles), as well as the model weights, striking a delicate balance between accurately capturing the concepts and avoiding overfitting. We employ a masked diffusion loss to enable handles to generate their assigned concepts, complemented by a novel loss on cross-attention maps to prevent entanglement. We also introduce union-sampling, a training strategy aimed to improve the ability of combining multiple concepts in generated images. We use several automatic metrics to quantitatively compare our method against several baselines, and further affirm the results using a user study. Finally, we showcase several applications of our method paper page:

AK

154,511 views • 3 years ago

"We will get our Jews" "You may be atheist" Extremists harass and abuse Australians in the centre of Sydney. The subtitles on the video as shared by the radical Islamist 'Stand4Palestine' page read 'We will get our jews". A bit of a Freudian slip? Why did Australia import this hate and how can we send it back?

"We will get our Jews" "You may be atheist" Extremists harass and abuse Australians in the centre of Sydney. The subtitles on the video as shared by the radical Islamist 'Stand4Palestine' page read 'We will get our jews". A bit of a Freudian slip? Why did Australia import this hate and how can we send it back?

Australian Jewish Association

18,634 views • 8 months ago

Most chiral molecules arise from carbons being bonded to 4 different atoms, which are called sterocenters. The makes the molecule have a different mirror image that cannot arise from simple rotation. But, you can have chiral molecules not from stereocenters. You can have chirality that doesn't come from a single point in the molecule. It comes from some global property. The classic example is helicene, which doesn't have any stereocenters, but has chirality because of hits helical structure. This means you cannot capture this molecule with a graph, and thus SMILES or a string representation cannot capture this. Of course natural language comes to the rescue (just say in words if it's left-handed or right-handed helix), but it's an interesting failure mode for viewing molecules as just a graph. Another example of a molecule with helical chirality is DNA. DNA is actually chiral in two ways, which is kind of confusing. It has both helical structure and stereocenters. You won't find the stereocenters ever flipped, but left-handed helical DNA can exist (called Z-DNA). Interestingly, making the flipped stereocenter of DNA could be part of an entire mirror organism (mirror RNA, DNA, AAs, sugars) that would then be potentially invisible to our immune systems. This has been recently proposed as a "mechanism" for how a runaway AI system could cause harm to Earth. I find it to be a pretty tedious and difficult way to cause harm, but it is intellectually cool. Anyway - this came up in a PhD defense and I have a lot of arcane knowledge about this I wanted to dump.

Most chiral molecules arise from carbons being bonded to 4 different atoms, which are called sterocenters. The makes the molecule have a different mirror image that cannot arise from simple rotation. But, you can have chiral molecules not from stereocenters. You can have chirality that doesn't come from a single point in the molecule. It comes from some global property. The classic example is helicene, which doesn't have any stereocenters, but has chirality because of hits helical structure. This means you cannot capture this molecule with a graph, and thus SMILES or a string representation cannot capture this. Of course natural language comes to the rescue (just say in words if it's left-handed or right-handed helix), but it's an interesting failure mode for viewing molecules as just a graph. Another example of a molecule with helical chirality is DNA. DNA is actually chiral in two ways, which is kind of confusing. It has both helical structure and stereocenters. You won't find the stereocenters ever flipped, but left-handed helical DNA can exist (called Z-DNA). Interestingly, making the flipped stereocenter of DNA could be part of an entire mirror organism (mirror RNA, DNA, AAs, sugars) that would then be potentially invisible to our immune systems. This has been recently proposed as a "mechanism" for how a runaway AI system could cause harm to Earth. I find it to be a pretty tedious and difficult way to cause harm, but it is intellectually cool. Anyway - this came up in a PhD defense and I have a lot of arcane knowledge about this I wanted to dump.

Andrew White 🐦‍⬛

15,039 views • 3 months ago

World Models are the path for some AI Models in the future. But how can we efficiently train these models to not only see the world the way humans do but to see the world in a new and unique way. By visualizing, what is normally sequenced audio patterns, we can derive much more insights. Here we see Paganini in a visual form that can than be described and transcribed into a World Model. We can observe connections in a manner that may not have been clear prior to the digitalization of music and sound in this way. The company with the most valuable potential in building a World Model is Tesla. Not that this type of visualization is being used, but that the mechanisms are in place, and the technology is in place for the company to thrive in this new form of AI.

World Models are the path for some AI Models in the future. But how can we efficiently train these models to not only see the world the way humans do but to see the world in a new and unique way. By visualizing, what is normally sequenced audio patterns, we can derive much more insights. Here we see Paganini in a visual form that can than be described and transcribed into a World Model. We can observe connections in a manner that may not have been clear prior to the digitalization of music and sound in this way. The company with the most valuable potential in building a World Model is Tesla. Not that this type of visualization is being used, but that the mechanisms are in place, and the technology is in place for the company to thrive in this new form of AI.

Brian Roemmele

57,424 views • 8 months ago

It's 2030 and you are reviewing humanoid robots. A Tesla. A Google. An Apple. An OpenAI. A Meta. A Figure. And a bunch of Chinese-made ones. Which one is best, and why? I think the Tesla understands the world much better. Why? There were eight Teslas around me on the freeway today. Start there. No other robot company has that data. But my robot is parked at the local high school twice a day. Its cameras see humans in all of our weirdness. How we move. Where we go. Where we walk. Who we talk with. What you are wearing. Whether your hair was combed this morning. That data will lead to robotics breakthroughs. Apple might keep up with its Vision Pro data, but it is too freaked out by the privacy implications of using said data. (On the front are six cameras and a couple of TOF -- Time Of Flight -- sensors that can see everything in your home in great detail). Google has a lot of data, for sure. All my: 1. Email. 2. Calendars. 3. Photos. 4. TV watching behavior. 5. Contacts. 6. Documents and spreadsheets. 7. Files. 8. Location data. So I expect Google's robot will be attractive to many. But how do you see the others shake out over the next five years? Make some guesses. But remember what an AI pioneer told me years ago about AI: it's all about the data. The Chinese ones have huge advantages: the Chinese have more data on their citizens, and many more citizens to boot AND they can make robots cheaper than we can. But now that you know OpenAI is building its own robot you have caught wind of what I've heard from many in San Francisco and Silicon Valley: that humanoid robots are the real prize of AI and will be highly profitable for those that can make them and find customers willing to buy them. Here, too, I learned long ago never to bet against Elon Musk. Will you?

It's 2030 and you are reviewing humanoid robots. A Tesla. A Google. An Apple. An OpenAI. A Meta. A Figure. And a bunch of Chinese-made ones. Which one is best, and why? I think the Tesla understands the world much better. Why? There were eight Teslas around me on the freeway today. Start there. No other robot company has that data. But my robot is parked at the local high school twice a day. Its cameras see humans in all of our weirdness. How we move. Where we go. Where we walk. Who we talk with. What you are wearing. Whether your hair was combed this morning. That data will lead to robotics breakthroughs. Apple might keep up with its Vision Pro data, but it is too freaked out by the privacy implications of using said data. (On the front are six cameras and a couple of TOF -- Time Of Flight -- sensors that can see everything in your home in great detail). Google has a lot of data, for sure. All my: 1. Email. 2. Calendars. 3. Photos. 4. TV watching behavior. 5. Contacts. 6. Documents and spreadsheets. 7. Files. 8. Location data. So I expect Google's robot will be attractive to many. But how do you see the others shake out over the next five years? Make some guesses. But remember what an AI pioneer told me years ago about AI: it's all about the data. The Chinese ones have huge advantages: the Chinese have more data on their citizens, and many more citizens to boot AND they can make robots cheaper than we can. But now that you know OpenAI is building its own robot you have caught wind of what I've heard from many in San Francisco and Silicon Valley: that humanoid robots are the real prize of AI and will be highly profitable for those that can make them and find customers willing to buy them. Here, too, I learned long ago never to bet against Elon Musk. Will you?

Robert Scoble

33,804 views • 1 year ago

Today in Munich, Germany. An important day, and there will be new steps toward our shared security – that of Ukraine and Europe. On the agenda is the first joint Ukrainian-German drone production enterprise, as well as bilateral and multilateral meetings with partners. We need more of our joint production, more of our resilience, more coordination and effectiveness of our shared security architecture in Europe. The most significant thing we can achieve together is ending the war with a dignified peace and creating reliable security guarantees for Ukraine and for all of Europe – so that no one in Europe is afraid of being left without protection. Thank you to everyone who is helping!

Today in Munich, Germany. An important day, and there will be new steps toward our shared security – that of Ukraine and Europe. On the agenda is the first joint Ukrainian-German drone production enterprise, as well as bilateral and multilateral meetings with partners. We need more of our joint production, more of our resilience, more coordination and effectiveness of our shared security architecture in Europe. The most significant thing we can achieve together is ending the war with a dignified peace and creating reliable security guarantees for Ukraine and for all of Europe – so that no one in Europe is afraid of being left without protection. Thank you to everyone who is helping!

Volodymyr Zelenskyy / Володимир Зеленський

125,987 views • 5 months ago

Dear Pioneers 🌏 We are living in a decisive moment! Pi Network has the potential to become a true revolution in the global financial landscape, but for that to happen, we must act wisely and united. We are millions of Pioneers around the world, driven by the same purpose: to create a decentralized, accessible, and fair financial system for all. The real value of Pi is not determined by the traditional market but by our confidence and engagement. The GCV of $314,159 represents much more than just a number – it symbolizes our conviction about Pi's potential. Our Strength Lies in the Community For Pi to reach its true value, we need to act strategically and with commitment. No great project can sustain itself without the support of its participants. If we want to see Pi shine, we must: ✅ Avoid having our Pi traded on exchanges prematurely, creating scarcity and strengthening its value ✅ Not accept selling it for prices lower than it truly deserves ✅ Acquire and withdraw Pi from exchanges, consolidating its strength in the market ✅ Use it in real transactions, promoting its growth as a global digital currency ✅ Spread awareness and encourage its daily use, expanding its acceptance Each Pioneer plays a crucial role in this process. The more we use and value Pi within the ecosystem, the more it will establish itself as an asset of great global impact. The Future Is in Our Hands We can allow speculators to dictate the value of Pi, or we can take control of our own destiny and ensure that it reaches its true potential. The decision is ours! If we act together, with strategy and determination, nothing can stop us from making Pi Network a milestone in cryptocurrency history. The time is now, and each of us is a fundamental part of this revolution. Let's strengthen Pi together and make the GCV of $314,159 an undeniable reality! Sérgio Cruz, Portugal GCV Ambassador 🇵🇹

Dear Pioneers 🌏 We are living in a decisive moment! Pi Network has the potential to become a true revolution in the global financial landscape, but for that to happen, we must act wisely and united. We are millions of Pioneers around the world, driven by the same purpose: to create a decentralized, accessible, and fair financial system for all. The real value of Pi is not determined by the traditional market but by our confidence and engagement. The GCV of $314,159 represents much more than just a number – it symbolizes our conviction about Pi's potential. Our Strength Lies in the Community For Pi to reach its true value, we need to act strategically and with commitment. No great project can sustain itself without the support of its participants. If we want to see Pi shine, we must: ✅ Avoid having our Pi traded on exchanges prematurely, creating scarcity and strengthening its value ✅ Not accept selling it for prices lower than it truly deserves ✅ Acquire and withdraw Pi from exchanges, consolidating its strength in the market ✅ Use it in real transactions, promoting its growth as a global digital currency ✅ Spread awareness and encourage its daily use, expanding its acceptance Each Pioneer plays a crucial role in this process. The more we use and value Pi within the ecosystem, the more it will establish itself as an asset of great global impact. The Future Is in Our Hands We can allow speculators to dictate the value of Pi, or we can take control of our own destiny and ensure that it reaches its true potential. The decision is ours! If we act together, with strategy and determination, nothing can stop us from making Pi Network a milestone in cryptocurrency history. The time is now, and each of us is a fundamental part of this revolution. Let's strengthen Pi together and make the GCV of $314,159 an undeniable reality! Sérgio Cruz, Portugal GCV Ambassador 🇵🇹

Doris Yin 东方紫莲🪷

25,065 views • 1 year ago

Did you know you can help us win, right now? Me and my Wisconsin Football teammates know that winning in the fall is a product of the preparation we put in this spring. The same is true for you! Make an impact that will be felt this fall by donating to @TVCCollective today! 🏈

Did you know you can help us win, right now? Me and my Wisconsin Football teammates know that winning in the fall is a product of the preparation we put in this spring. The same is true for you! Make an impact that will be felt this fall by donating to @TVCCollective today! 🏈

TACKETT CURTIS

13,193 views • 2 years ago

Did you know you can help us win, right now? Me and my Wisconsin Football teammates know that winning in the fall is a product of the preparation we put in this spring. The same is true for you! Make an impact that will be felt this fall by donating to @TVCCollective today!🏈

Did you know you can help us win, right now? Me and my Wisconsin Football teammates know that winning in the fall is a product of the preparation we put in this spring. The same is true for you! Make an impact that will be felt this fall by donating to @TVCCollective today!🏈

Tyler Van Dyke

14,952 views • 2 years ago

As part of our Charting Crypto quarterly report, we ask several leading voices in crypto to contribute a chart that they believe is the most important crypto trend today. This quarter, Grayscale highlighted AI in crypto and its potential upside.

As part of our Charting Crypto quarterly report, we ask several leading voices in crypto to contribute a chart that they believe is the most important crypto trend today. This quarter, Grayscale highlighted AI in crypto and its potential upside.

Coinbase Institutional 🛡️

44,375 views • 11 months ago