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 regulatory activity. For the full read ➡️show more

🧬 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!show more

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. 🧵↓show 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:show more

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.show more

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:show more

🚨 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.show more

This fact absolutely shatters evolution. ...And makes the intelligent... design in Life certain. All the systems in Life that make things function - like everything that enables birds to fly - require a whole set of complex interconnected parts. Nothing works in isolation. Something evolutionists overlook is how the nature of all these systems are intricately interconnected. Every part relies on something else to make it work. You need the whole system, down to the DNA itself, or the function fails. This coordinattion between so many systems makes step-by-step evolution all but impossible. For instance... A wing isn’t just bones and feathers (or membrane). A wing requires a certain type of hollow bones, which the alleged ancestors of birds didn't have. And wings by themselves are useless - what reproductive benefit would wings have without the accompanying systems that lead to actual flight (the simultaneous requirements for bone pneumatization, muscle attachment sites, feather or membrane development, and the regulatory changes that control all of them)? Wings without these features would be harmful. Hollow bones without flight would be detrimental. The step-by-step path leading from non-bird to flying birds is filled with easily killed, unselectable intermediates. This is where evolutionists constantly fail - they look at modification in isolation, without considering that these systems are large, interconnected networks of functional parts all working together. And it all starts at the genetic level, from the DNA itself. DNA genes code for proteins. Regulatory information organizes when these proteins are built and how much should be made. Further regulatory systems coordinate where these proteins go after they’re built. And yet more informational networks place the proteins into the final system in coordination with other proteins. Then these protein systems are fit together to make entire organs, tissues, bones, etc. All of these systems and processes are coordinated from the DNA - which means major modification like turning a fish fin into a bird wing requires many coordinated DNA changes across the entire network. One change at a time simply cannot lead to the coordination of an entire multi-part coordinated system like this. A mutation that changes one protein would need another coordinated mutation to fit that mutated protein into the right place, which would require other proteins to be mutated to fit together into that system, which would also require yet more regulatory mutations to keep everything coordinated... Nothing works in isolation. It's all connected. Which is why it can't evolve one step at a time. One step at a time does nothing. Life requires all or nothing systems. Only intelligence can engineer all or nothing systems.show more

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 manipulationshow more

AI builders rely on a cloud that moves at... their pace. Today, IREN takes another step forward with the completion of our acquisition of Mirantis. By bringing together IREN’s owned and operated data centers and compute with Mirantis’ flexible, interoperable software layer, we’re giving customers greater choice and control in how they deploy and scale AI workloads. Developers and enterprises want flexibility as the AI landscape evolves. We're building an open foundation that grows with you, so you’re ready for what's next. Read more:show more

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 🫡show more

Tyler didn't take a shot and was probably just... honeydicked to show up in the morning to be seen on camera.. his rifle had dust in the barrel and his DNA was on it but degraded. They didn't find his fingerprints or his DNA on the roof even though he GI Joe'd from the rooftop without gloves. We don't have a single frame of video that shows the rifle near the crime scene and we don't have his license plate scanned even though he parked in a paid lot that processes payments with the license plate. The microphone wasn't in Charlie's possession and the only time he saw it was when his AV team clipped it on its side underneath his shirt... the same AV team that makes a selfie video while hiding behind a wall saying that "they killed Charlie" and then goes and pulls the SD cards from the cameras that were around Charlie. As far as we know that microphone could have had explosives in it for months. The walkie talkies were used by Hezbolla for years before the Israelis blew them up remotely.show more

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:show more

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.show more

"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?show more

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.show more

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?show more

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!show more

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 🇵🇹show more