How Zak Brown Led the Revival of McLaren Racing
The CEO of the F1 champion-winning team discusses the hurdles he faced reversing McLaren’s negative momentum.
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Enabling small language models to solve complex reasoning tasks
As language models (LMs) improve at tasks like image generation, trivia questions, and simple math, you might think that human-like reasoning is around the corner. In reality, they still trail us by a wide margin on complex tasks. Try playing Sudoku with one, for instance, where you fill in numbers one through nine in such a way that each appears only once across the columns, rows, and sections of a nine-by-nine grid. Your AI opponent will either fail […]
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Bringing state-of-the-art Gemini translation capabilities to Google Translate
We’re bringing Gemini’s state-of-the-art translation model to Google Translate for text, and more new features.
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Stay Ahead of AI Risks – Free Live Session for Tech Leaders
Exclusive working session about trustworthy AI, for senior tech leaders. View PowerPoint presentation, here. AI isn’t slowing down, but poorly planned AI adoption will slow you down. Hallucinations, security risks, bloated compute costs, and “black box” outputs are already tripping up top teams, burning budgets, and eroding trust. That’s why this session blends three things you can’t get from a typical AI webinar: Practical expertise: GenAI pioneer Vincent Granville will share a real-world framework for deploying hallucination-free, secure, and […]
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How would you defend nap?
Why is nap better that any other ethical system? submitted by /u/unholy_anarchist [link] [comments]
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Decentralized Computation: The Hidden Principle Behind Deep Learning
Most breakthroughs in deep learning — from simple neural networks to large language models — are built upon a principle that is much older than AI itself: decentralization. Instead of relying on a powerful “central planner” coordinating and commanding the behaviors of other components, modern deep-learning-based AI models succeed because many simple units interact locally […] The post Decentralized Computation: The Hidden Principle Behind Deep Learning appeared first on Towards Data Science.
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BBVA and OpenAI collaborate to transform global banking
BBVA is expanding its work with OpenAI through a multi-year AI transformation program, rolling out ChatGPT Enterprise to all 120,000 employees. Together, the companies will develop AI solutions that enhance customer interactions, streamline operations, and help build an AI-native banking experience.
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What Is Retrieval-Augmented Generation, aka RAG?
Editor’s note: This article, originally published on Nov. 15, 2023, has been updated. To understand the latest advancements in generative AI, imagine a courtroom. Judges hear and decide cases based on their general understanding of the law. Sometimes a case — like a malpractice suit or a labor dispute — requires special expertise, so judges send court clerks to a law library, looking for precedents and specific cases they can cite. Like a good judge, large language models […]
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Microsoft AI Releases VibeVoice-Realtime: A Lightweight Real‑Time Text-to-Speech Model Supporting Streaming Text Input and Robust Long-Form Speech Generation
Microsoft has released VibeVoice-Realtime-0.5B, a real time text to speech model that works with streaming text input and long form speech output, aimed at agent style applications and live data narration. The model can start producing audible speech in about 300 ms, which is critical when a language model is still generating the rest of its answer. Where VibeVoice Realtime Fits in the VibeVoice Stack? VibeVoice is a broader framework that focuses on next token diffusion over continuous […]
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A faster problem-solving tool that guarantees feasibility
Managing a power grid is like trying to solve an enormous puzzle. Grid operators must ensure the proper amount of power is flowing to the right areas at the exact time when it is needed, and they must do this in a way that minimizes costs without overloading physical infrastructure. Even more, they must solve this complicated problem repeatedly, as rapidly as possible, to meet constantly changing demand. To help crack this consistent conundrum, MIT researchers developed a […]
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