We’re excited to introduce ShinkaEvolve: An open-source framework that... evolves programs for scientific discovery with unprecedented sample-efficiency. Blog: Code: Like AlphaEvolve and its variants, our framework leverages LLMs to find state-of-the-art solutions to complex problems, but using orders of magnitude fewer resources! Many evolutionary AI systems are powerful but act like brute-force engines, burning thousands of samples to find good solutions. This makes discovery slow and expensive. We took inspiration from the efficiency of nature. ‘Shinka’ (進化) is Japanese for evolution, and we designed our system to be just as resourceful. On the classic circle packing optimization problem, ShinkaEvolve discovered a new state-of-the-art solution using only 150 samples. This is a big leap in efficiency compared to previous methods that required thousands of evaluations. We applied ShinkaEvolve to a diverse set of hard problems with real-world applications: 1/ AIME Math Reasoning: It evolved sophisticated agentic scaffolds that significantly outperform strong baselines, discovering an entire Pareto frontier of solutions trading performance for efficiency. 2/ Competitive Programming: On ALE-Bench (a benchmark for NP-Hard optimization problems), ShinkaEvolve took the best existing agent's solutions and improved them, turning a 5th place solution on one task into a 2nd place leaderboard rank in a competitive programming competition. 3/ LLM Training: We even turned ShinkaEvolve inward to improve LLMs themselves. It tackled the open challenge of designing load balancing losses for Mixture-of-Experts (MoE) models. It discovered a novel loss function that leads to better expert specialization and consistently improves model performance and perplexity. ShinkaEvolve achieves its remarkable sample-efficiency through three key innovations that work together: (1) an adaptive parent sampling strategy to balance exploration and exploitation, (2) novelty-based rejection filtering to avoid redundant work, and (3) a bandit-based LLM ensemble that dynamically picks the best model for the job. By making ShinkaEvolve open-source and highly sample-efficient, our goal is to democratize access to advanced, open-ended discovery tools. Our vision for ShinkaEvolve is to be an easy-to-use companion tool to help scientists and engineers with their daily work. We believe that building more efficient, nature-inspired systems is key to unlocking the future of AI-driven scientific research. We are excited to see what the community builds with it! Learn more in our technical report:show more

It’s more than a little daunting to set out... to expand and improve the identity system for a company and brand like Stripe. But we knew we had to — the existing one had served us well, but wasn’t up to the task anymore. Our brand system required new and improved tools to scale with our ever growing audiences, new products, global footprint, and more. This update introduces material improvements to infographics, advertising, type styles, and more. While the wordmark remains unchanged, we’re using the dot of the ‘i’ (called the “tittle”), a parallelogram pointing up and to the right, to serve as our identifying symbol. We’re also using it as an ever evolving storytelling device to use when talking about our many great users (you can see the latest brand campaign in SF and NYC doing just that). Anyone who has ever worked on the refresh and expansion of an existing system for a large company knows that it is no small endeavor. Crafting impactful solutions, building alignment, creating extensible guidelines, building toolkits, and orchestrating rollout requires a ton of resilience. Here’s to the team that continually inspires me with their dedication, rigor, taste, and exceptional vibes. Great work and thank you to the Brand Studio folks, and of course our many many amazing and invaluable friends and collaborators across the company who all helped shape the work. And a special thank you to a handful of creative agencies that helped us along the way.show more

There is only one reason to share truth. And... no it has nothing to do with money- and everything to do about helping God move. Peace is the prize- a better world for everyone is the prize. We make SACRIFICES for things we want most in this world. Christ made the ultimate sacrifice If He can do that for us FREE of charge- we owe it to each other to work TOGETHER to make the world a better place- despite the toll and sacrifice. A level playing field- where we can all work hard and do our best to succeed- that is the payout. A better world for all We’re not here for just ourselves- otherwise the second commandment wouldn’t be like the first- love your neighbor as yourself. This world gets better the sooner we all wake up. Information is free- we collect and share it for free in hopes that it keeps spreading. Only working TOGETHER can we win. We are meant to move these messages for God so that humanity can wake up- this plan is designed that way- working together The Lord is ONE. We are bound as a family by Our Father in Heaven. We are apart of Him and He is apart of all of us. We are billions of little pieces of the Lords gift of life. We’ve been separated and pushed apart because it makes us weak. We were designed to be powerful by the love we draw from Creator and push through creation. We are ONE with Our Holy Father 🙏💗 Be EXCELLENT to each other frensshow more

We just launched our biggest creator partnership to date.... We're excited about it. It's done really well so far. A few of our big bets for this year and beyond are: - creator obsession - partnerships - In real life community activations - sampling - overall brand building Something that is definitely newer to us, and we're definitely late getting into, but the best place to start is today. We launched a product with a well-known creator last week. That has gone really well and will unfortunately be out of stock on a bunch of shades soon. We did an in-person event with her at, 8 months pregnant today at one of our stores. It was our first time ever hanging blister packs to sample. We had a bunch of blister packs and a bunch of agile trucks, plus some other out-of-home. It's all a big content play, but also building community and introing people to the brand and getting samples in as many people's hands as possible. We just bought a rivian and wrapped it for sampling events. Hoping to give away 7 figures in samples this year and next. We started with 1 but I’m gonna pull the trigger on a few more once we see signs of traction. We’re opening 12 stores this year and doubling down on IRL, community, and sampling. We have another brand partnership in a few weeks with a big IRL component as well. Excited to learn new things and keep pushing into building a brand, community, and meeting people IRL.show more

Our aero kit for the 2024+ Model 3 Performance... is designed using CFD to enhance performance while preserving Tesla’s renowned efficiency. Shown here is the exploded view of the aero kit parts to show how we accomplish our goal: to work with the Model 3 Performance foundation without disturbing it. The kit now delivers 1896N of downforce, shifting the car from net lift to substantial downforce with a minimal drag increase of just 1.93%. This is achieved through advanced aerodynamic techniques, such as splitter tunnels that enhance front ground effect—features rarely seen on street-legal vehicles. The kit enhances downforce in areas that already have high-pressure air, such as above the grille, over the side inlets, and on top of the front splitter, but also introduces entirely new shapes like the front undertray. Airflow management around the wheels and side skirts is critical for reducing drag and offsetting the added drag from downforce-generating surfaces. Additionally, placing a wing that is highly optimized to minimally disturb Tesla’s refined wake is crucial for maintaining efficiency. While we’re working out a few more final touches with our production run, we are just as excited to reach out to those who have patiently waited and look forward to providing order updates soon!show more

A team of Ukrainian experts is working in Qatar,... sharing our experience and expertise. I met with our team here today and received a briefing on their work. Our experts have already conducted an overall assessment of the security situation, Qatar’s capabilities to counter aerial threats, and have developed concrete solutions to strengthen the protection of its airspace. And today, during my meeting with the Amir of the State of Qatar, Sheikh Tamim bin Hamad Al Thani, it was important for me to hear such a high assessment of our team’s work and appreciation for their consultations. Ballistic missile and drone attacks are currently the biggest challenge here in the region. And while only air defense systems can effectively counter ballistic threats, in Ukraine, we have developed other, significantly more cost-effective solutions to combat drones. These solutions have already proven their effectiveness against various types of drones, which is why Qatar is so interested in our experience. Ukraine has always said that we are ready to share our expertise and help those who can also help us strengthen our own protection in Ukraine. Qatar is ready for long-term cooperation across various areas. It is important to restore stability in the region so that no one suffers from Iran's terrorist strikes. And we support an approach where, by helping one another, we increase security worldwide.show more

1/ Gemini 2.5 is here, and it’s our most... intelligent AI model ever. Our first 2.5 model, Gemini 2.5 Pro Experimental is a state-of-the-art thinking model, leading in a wide range of benchmarks – with impressive improvements in enhanced reasoning and coding and now #1 on Arena by a significant margin. With a model this intelligent, we wanted to get it to people as quickly as possible. Find it on Google AI Studio and in the Google Gemini for Gemini Advanced users now – and in Vertex in the coming weeks. This is the start of a new era of thinking models – and we can’t wait to see where things go from here.show more

Frontier drug discovery programs require frontier capabilities. Today, we’re... excited to share that BMS will be using Chai’s models to support the discovery of new therapeutics. Since rolling out Chai-3 to partners at the start of this year, we’ve partnered with Eli Lilly and Company, Novartis, Pfizer Inc., argenx, and now Bristol Myers Squibb. Many of the world’s leading biopharma companies are now using our models to go after diseases. Scientific discovery is the domain where access to frontier AI matters the most. At Chai Discovery, we’ve seen first hand how our latest model generations can make the difference between discovering a molecule and not. We’re excited to work with Bristol Myers Squibb to break new ground in medicine and science.show more

$zkHive X $DONGO 🤝 We are excited to announce... our partnership with Dongo AI ! Dongo AI is a platform designed to simplify and connect the expansive world of cryptocurrency for everyday users. Using their product users can research their preferred tokens and pose questions about the project, leveraging our AI's technology. We’re happy to announce that #zkHive is going to be one of the first projects to be integrated into Dongo’s upcoming platform launch. In addition #HiveBot will be integrated into Dongo’s community, and our security APIs will be used to secure the thousands of users of the Congo ecosystem! Thanks to the AI platform that DONGO is building, $ZKHIVE is going to protect thousands of new users! This is another great step by both parties to promote AI and security in the space!show more

Dear Tarun Chitra 1. We are the original creators... of DeSci back in 2016. What DeSci has become today is largely unrelated with its original model of producing rigorous peer-reviewed scientific studies published in reputable medical journals. The model we introduced. We are tirelessly fighting against pseudoscience, and we are showing the world that people can understand the difference between legit science and pseudoscience with the success of $INNBCV. Yes, meritocracy is possible in crypto. Even against all odds. 2. We are the only project in the entire crypto space that ever funded, performed, and published highly innovative HIV cure research ( We are the project that produced the first peer-reviewed study on blockchain-based biomedical data storage in the world’s most reputable scientific network, Springer Nature ( $INNBCV is not for the privileged few; it is for the many. We resisted all the pressure from those who wanted us to provide big allocations to VIPs of other DAOs “because it is good for the marketing” and put our users first, ensuring a fair launch, a launch for the people, and they turned $70k into $2,000,000. $INNBCV shows that you can have a sustainable model, provided you are backed by actual science. And thanks to the amazing guys at daos.fun baoskee and Solana community. Behind our project there is the sweat and blood of years of work to produce publications in the most reputable medical journals. Just to put things into perspective, it took us 3 years to publish our latest work in Springer Nature. 3. Unlike many other projects, we had no ICO/VCs, meaning we had to prove ourselves every single day because we are only supported by our community. If we deliver products, we survive; it is either publish or perish for us, and that’s why we have such a close connection to our community. $INNBCV is a struggler, $INNBCV is a survivor, $INNBCV is not for the privilege of the few but for the people. Our community makes it possible by supporting us. You guys are the real heroes.show more

Everything began with a seed, a seed of innovation... and vision, planted in the fertile ground of technology. This is the essence of XRootAI, where we delve into the roots of artificial intelligence to cultivate bespoke #AI solutions. Our mission is to empower companies, communities, and projects with tailored artificial intelligence that drives progress and innovation. As a pioneering force in the crypto landscape, XRootAI not only redefines the boundaries of AI but also integrates it with the dynamic world of crypto through our unique token #XROOTAI. Welcome to XRootAI – The root of artificial intelligence, where every solution is a testament to the power of inception and growth.show more

The newest version of our Almanac preprint is out,... and just in time for our demo at the Stanford AIMI Symposium 2023! Almanac is a retrieval-augmented LLM that provides up-to-date and verifiable answers to medical queries. Link: We benchmark our approach on a novel dataset of clinical scenarios (n = 130) evaluated by a panel of 5 board-certified & resident physicians, and demonstrate significant increases in factuality (mean of 18% at p-value < 0.05) across all specialties. More interestingly, because the retrieved data acts as a single source of truth, we find retrieval-based LLMs to be more robust to prompt injection and manipulation! Future work will involve expanding the scope of our dataset to more specialties and multimodal settings. #Medtwitter #MedEdshow more

There is something beautiful about the instinct of a... child to protect another. Before we learn the divisions that separate us, before we are taught to fear or distrust one another, there is within us a powerful capacity to care, to help, to protect, and to love. And yet we live in a world where our algorithms and media too often amplify the worst of humanity. The cruelty, the outrage, the selfishness, the division. Meanwhile, millions upon millions of acts of kindness, decency, grace, and compassion happen every day, often unseen and uncelebrated. We can begin to believe the lie that cruelty defines us, that selfishness is our nature, that the ties that divide us are stronger than the bonds that unite us. But there is so much goodness in this world. So many people looking out for one another. So many people stepping forward to help, to serve, to protect. We are at our best when we recognize that we belong to one another. That our strength is found not in selfishness but in service, not in division but in community, not in indifference but in love. And sometimes it takes a little child, stepping forward to protect those smaller than herself, to remind us of this profound truth. May we see more of this. May we be more of this.show more

🌠Today, we’re excited to relaunch Airtable as the AI-native... app platform, combining the magic of vibe coding business apps with real production-readiness and scalability, and embedding them with an army of agents that automate thousands of hours of work in seconds. Instead of just adding more AI capabilities to our existing platform, we treated this as a refounding moment for the company. We started with a clean-slate imagining of the ideal form factor for building apps in the agentic era. (If you want to skip all the backstory and just try it out, you can just go to All new signups get the new AI experience, and existing accounts can switch over using this link: Thread and demos below👇show more

What if you kept asking an LLM to "make... it better"? In some recent work at FAIR, we investigate how we can efficiently use RL to fine-tune LLMs to iteratively self-improve on their previous solutions at inference-time. Training for iterated self-improvement can be costly. The naive approach to training for K self-improvement steps leads to K times the number of rollout steps per episode. We introduce Exploratory Iteration (ExIt), an RL-based automatic curriculum method that bootstraps diverse training distributions of self-improvement tasks by upcycling the LLM's own responses at previous turns as the starting points for both self-improvement and *self-divergence.* In order to decide what task to train on next, the curriculum prioritizes sampling of partial turn histories that led to higher return variance in its GRPO group (a learnability score that comes for free). This automatic curriculum over the bootstrapped task space teaches the model how to perform iterated self-improvement while only ever training the model on single-step self-improvement tasks. We look at ExIt's impact in both single-turn (contest math problems) and multi-turn (BFCLv3 multi-turn tasks), as well as MLE-bench, where the LLM is run in a search scaffold to produce solutions to real Kaggle competitions. Across these eval settings, we find ExIt produces models with greater capacity for inference-time self-improvement compared to GRPO. Notably, ExIt models can self-improve on test tasks for many more steps than the typical solution depth encountered during training, including a 22% improvement in MLE-bench performance compared to GRPO.show more

We’re excited to introduce Text-to-LoRA: a Hypernetwork that generates... task-specific LLM adapters (LoRAs) based on a text description of the task. Catch our presentation at #ICML2025! Paper: Code: Biological systems are capable of rapid adaptation, given limited sensory cues. For example, our human visual system can quickly adapt and tune its light sensitivity to our surroundings. While modern LLMs exhibit a wide variety of capabilities and knowledge, they remain rigid when adding task-specific capabilities. Traditionally, customizing these models requires gathering large datasets and performing often expensive, time-consuming fine-tuning for specific applications. To bypass these limitations, Text-to-LoRA (T2L) meta-learns a “hypernetwork” that takes in a text description of a desired task, as a prompt, and generates a task-specific LoRA that performs well on the task. In our experiments, we show that T2L can encode hundreds of existing LoRA adapters. While the compression is lossy, T2L maintains the performance of task-specifically tuned LoRA adapters. We also show that T2L can even generalize to unseen tasks given a natural language description of the tasks. Importantly, Text-to-LoRA is parameter-efficient. It generates LoRAs in a single, inexpensive step, based solely on a simple text description of the task. This approach is a step towards dramatically lowering the technical and computational barriers, allowing non-technical users to specialize foundation models using plain language, rather than needing deep technical expertise or large compute resources.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

Happy to share RSI-top: a framework that helps autonomous... research agents escape exploration collapse 📈 RSI-top outperforms OpenEvolve and ShinkaEvolve by up to 15% on kernel optimization tasks and achieves a 77.3% medal rate on MLE-Bench Lite. We developed metrics for retrieving useful past trajectories and proposed 3 diversity control mechanisms that encourage new ideas, perspectives, and starting points when progress stalls. 📄 Blog: Work led by Yuzhen Mao, with incredible collaborators Shayan Talaei and Azalia Mirhoseinishow more

We are releasing AutoResearchExam, a benchmark on open-ended machine... learning and engineering tasks. Our benchmark covers seven research areas including model training, data curation, AI safety and interpretability. In each task, we give agents 24 hours with a CPU or GPU machine to develop and improve their solutions through experiments and feedback. We measure both speed and quality with a combined score. Our benchmark has a unique feature: testing if agents create improvements that hold up on data they never see. We find that AI research agents often overfit as they try to improve. We see an interesting head-to-head comparison at the frontier: Astra starts the strongest and holds the lead for up to 19 hours but Fable 5.1 catches up and gets the top performing spot in the final hours. Qwen3.8 Max, Gemini 3.8 Flash and Grok 4.6 all sit on the cost-performance Pareto frontier, giving strong options at lower API budgets. Anthropic's Opus and Fable retain nearly all their validation performance on hidden tests, with gaps of 1.1% and 2.9%. Astra's improvement over Sol extends to generalization too, with that gap falling from 6.9% to 1.7%. (1/n)show more