2025-12-15

In a debate with DeepMind researcher Adam Brown, Meta's Chief AI Scientist Yann LeCun explained why Large Language Models (LLMs) represent a dead end on the path to human-like intelligence. The fundamental issue, LeCun argues, lies in the way these models make predictions.
The article The case against predicting tokens to build AGI appeared first on THE DECODER.
[...]2025-10-21
DeepSeek, the Chinese artificial intelligence research company that has repeatedly challenged assumptions about AI development costs, has released a new model that fundamentally reimagines how large l [...]
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DeepSeek continues to push the frontier of generative AI...in this case, in terms of affordability.The company has unveiled its latest experimental large language model (LLM), DeepSeek-V3.2-Exp, that [...]
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Non-fungible tokens (NFTs) are the most popular digital assets today, capturing the attention of cryptocurrency investors, whales and people from around the world. People find it amazing that some u [...]
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Enterprises expanding AI deployments are hitting an invisible performance wall. The culprit? Static speculators that can't keep up with shifting workloads.Speculators are smaller AI models that w [...]
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Researchers at Mila have proposed a new technique that makes large language models (LLMs) vastly more efficient when performing complex reasoning. Called Markovian Thinking, the approach allows LLMs t [...]
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Enterprises can now harness the power of a large language model that's near that of the state-of-the-art Google’s Gemini 3 Pro, but at a fraction of the cost and with increased speed, thanks to [...]
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For all their superhuman power, today’s AI models suffer from a surprisingly human flaw: They forget. Give an AI assistant a sprawling conversation, a multi-step reasoning task or a project spanning [...]