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Introducing SoftMatcha 2: A Fast and Soft Pattern Matcher for Trillion-Scale Pre-Training Corpora What lies within a trillion-scale pre-training corpus? Can you truly guarantee your benchmarks are uncontaminated simply because there are no exact string matches? Alongside several research institutions in Japan, Sakana AI is proud to have collaborated...

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Sakana AI

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The infrastructure for working with video data at scale barely exists. Grass Video Search is our first step in changing that. You can now find anything in a video based on the contents of its frames, not just transcripts or tags. Over the last several months, the Grass Foundation has quietly assembled one of the largest video datasets in history: over a billion videos from across the public web, and is segmenting them by scene with VLM annotations of keyframes. This dataset is now searchable, so you can find the exact moment a visual, pattern, or concept appears. Curation has always been the bottleneck in video analysis. We built a system that automates it. This is just the beginning. Over 4 billion additional videos are queued for processing, and the index is growing daily. We’re opening access to a limited set of collaborators. If you’re a researcher, journalist, or nonprofit working with video, archives, or large-scale analysis, we’d love to hear from you.

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NEW: Elon Musk says he thinks he can reduce the deficit by $1 Trillion next year, says it will cause a cascading effect for Americans. “I think we can take a trillion dollars out of the out of the deficit next year.” “We have a $2 trillion deficit, which is a far in excess of economic growth. If we can get that deficit in half, from 2 trillion to 1 trillion, and we can get the economic growth to match that 1 trillion growth in the money supply, that means there will be no inflation.” “Interest rates will drop, credit card interest down, mortgage interest down, car payment interest down, and prices at the store stay the same.” “That is a great outcome for people and I think we can do it.”

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Progressively Optimized Local Radiance Fields for Robust View Synthesis paper page: present an algorithm for reconstructing the radiance field of a large-scale scene from a single casually captured video. The task poses two core challenges. First, most existing radiance field reconstruction approaches rely on accurate pre-estimated camera poses from Structure-from-Motion algorithms, which frequently fail on in-the-wild videos. Second, using a single, global radiance field with finite representational capacity does not scale to longer trajectories in an unbounded scene. For handling unknown poses, we jointly estimate the camera poses with radiance field in a progressive manner. We show that progressive optimization significantly improves the robustness of the reconstruction. For handling large unbounded scenes, we dynamically allocate new local radiance fields trained with frames within a temporal window. This further improves robustness (e.g., performs well even under moderate pose drifts) and allows us to scale to large scenes. Our extensive evaluation on the Tanks and Temples dataset and our collected outdoor dataset, Static Hikes, show that our approach compares favorably with the state-of-the-art.

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Introducing RAGs v3 🌟: Build a RAG bot that can also search the web 🌐, to find answers that aren’t immediately in its corpus. Do this all in natural language, not code! 💬 Get a better experience than ChatGPT + Bing ⚡️ We used our integration with Metaphor - a search engine designed for LLMs - to pull in relevant text from the internet. Additionally: - you can now view the tools that the agent is using. - note: web search is only accessible for our OpenAI agent Check out the video below, and get started with the repo today. Repo:

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76,366 Aufrufe • vor 2 Jahren

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50,477 Aufrufe • vor 4 Tagen

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Today we announced our new Fairwater datacenter in Atlanta, connected with our first Fairwater site in Wisconsin and our broader Azure footprint to create the world’s first AI superfactory. Fairwater exemplifies our vision for a fungible fleet: infra that can serve any workload, anywhere, on fit-for-purpose accelerators and network paths, with maximum performance and efficiency. AI workloads have evolved beyond large-scale pre-training. Today, they encompass fine-tuning, reinforcement learning (RL), synthetic data generation, evaluation pipelines, and more. Fairwater is built to support this full lifecycle: Max density: Fairwater’s two-story design and liquid cooling system lets us place racks in three dimensions and pack them with GPUs as densely as possible, minimizing cable runs and improving latency and effective bandwidth. Fleet: Each Fairwater DC can integrate hundreds of thousands of the latest NVIDIA GPUs into a single coherent cluster. This provides flexible infra that can support the full spectrum of workloads, and ensure no GPU is left unnecessarily idle. And that’s on top of the more than 100,000 GB300s coming online this quarter alone for inference across the rest of our fleet. For us, it’s all about turning every gigawatt into the maximum number of useful tokens. Not every GW is created equal! Planet-scale: Every Fairwater DC will connect through our continent-spanning AI WAN to prior generations of AI supercomputers, forming a truly fungible pool of compute. This enables developers to scale beyond the capacity of a single site and dynamically land workloads on the right infra for their needs. Together, these innovations let us bring together different generations of silicon and AI systems across DCs and geos into a single elastic system that scales seamlessly across training and inference workloads And this elastic AI capacity is all available alongside all the other cloud services (compute, storage, databases, app services) that AI agents and workloads need. This is what we mean when we talk about building a fungible fleet – a single, unified platform that pushes the limits of performance per watt and per dollar. Read more:

Satya Nadella

906,810 Aufrufe • vor 7 Monaten

Then came one of the biggest financial updates of the meeting...from Treasury Secretary Scott Bessent. What he revealed was staggering. Bessent said that America is now pulling in RECORD tariff revenues...between $500 BILLION and $1 TRILLION a year...and the budget deficit is already down 26% from Biden’s last year in office. These are not small numbers. Bessent explained how Trump flipped the system on its head. The days of unbalanced international trade are over, and with that comes a massive influx of cash directly affecting America’s deficit. “On the international front you have a leveled the international trading system whereby countries took advantage of us and that’s over. It’s OVER.” “The Treasury Department is in is taking in record tariff revenues that I had been saying was running at a rate of 300 billion a year.” “You chastised me for saying that—number is too low. And as usual, you we’re right, that we had a substantial, jump from July to August, and I think we’re going to see a bigger jump from August to September.” “So I think we could be on our way, well, over half a trillion, maybe the, towards the trillion dollar number.” “This administration, your administration, has made a meaningful dent in the budget deficit.” Even the CBO, which often clashes with the Trump administration, had to concede: the deficit is projected to drop by $4 trillion over the next decade. “The average budget deficit during this term is 26% less than the last 12 months under Biden and even the CBO, and we don’t agree with CBO on everything as you said, last Friday—had to admit that they believe over the next ten years the budget deficit will be 4 trillion lower than they had previously scored.” And according to Bessent, that number could go even higher. “4 trillion: 3.3 trillion of tariff income, 700 billion of lower interest cost, and, you know, I would expect that that number could go up from here.”
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Then came one of the biggest financial updates of the meeting...from Treasury Secretary Scott Bessent. What he revealed was staggering. Bessent said that America is now pulling in RECORD tariff revenues...between $500 BILLION and $1 TRILLION a year...and the budget deficit is already down 26% from Biden’s last year in office. These are not small numbers. Bessent explained how Trump flipped the system on its head. The days of unbalanced international trade are over, and with that comes a massive influx of cash directly affecting America’s deficit. “On the international front you have a leveled the international trading system whereby countries took advantage of us and that’s over. It’s OVER.” “The Treasury Department is in is taking in record tariff revenues that I had been saying was running at a rate of 300 billion a year.” “You chastised me for saying that—number is too low. And as usual, you we’re right, that we had a substantial, jump from July to August, and I think we’re going to see a bigger jump from August to September.” “So I think we could be on our way, well, over half a trillion, maybe the, towards the trillion dollar number.” “This administration, your administration, has made a meaningful dent in the budget deficit.” Even the CBO, which often clashes with the Trump administration, had to concede: the deficit is projected to drop by $4 trillion over the next decade. “The average budget deficit during this term is 26% less than the last 12 months under Biden and even the CBO, and we don’t agree with CBO on everything as you said, last Friday—had to admit that they believe over the next ten years the budget deficit will be 4 trillion lower than they had previously scored.” And according to Bessent, that number could go even higher. “4 trillion: 3.3 trillion of tariff income, 700 billion of lower interest cost, and, you know, I would expect that that number could go up from here.”

The Vigilant Fox 🦊

238,581 Aufrufe • vor 9 Monaten