Podcasts & Talks
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters (Paper)
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters (Paper)
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Happy 4th of July! 🎆 Made with Veo 3 in Gemini
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Podcasts & Talks
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters (Paper Explained)
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters (Paper Explained)
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Podcasts & Talks
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
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Funding & Business6 days agoKayak and Expedia race to build AI travel agents that turn social posts into itineraries
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Jobs & Careers6 days ago
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Mergers & Acquisitions6 days ago
Donald Trump suggests US government review subsidies to Elon Musk’s companies
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Funding & Business6 days ago
Rethinking Venture Capital’s Talent Pipeline
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Jobs & Careers6 days ago
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Funding & Business3 days ago
Sakana AI’s TreeQuest: Deploy multi-model teams that outperform individual LLMs by 30%
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Jobs & Careers3 days ago
Ilya Sutskever Takes Over as CEO of Safe Superintelligence After Daniel Gross’s Exit
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Jobs & Careers6 days ago
Telangana Launches TGDeX—India’s First State‑Led AI Public Infrastructure
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Funding & Business3 days ago
Dust hits $6M ARR helping enterprises build AI agents that actually do stuff instead of just talking
