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Skepticism is key to getting AI to do exactly what you...

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Anthropic

Snap’s latest AI-powered tool targets SMBs

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Anthropic

Roblox earnings: Why it paid out $280 Million to creators during...

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Anthropic

Under a Welsh Airfield, 2,000-Year Old Chariot Parts were Found

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Researchers create reasoning model under $50 that performs similar to OpenAI’s...

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Report: OpenAI’s former CTO, Mira Murati has recruited OpenAI cofounder John...

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Google lifts self-imposed ban against AI being used in weapons and...

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AI is ‘an energy hog,’ but DeepSeek could change that

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Reframing digital transformation through the lens of generative AI

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Uber CEO warns that robotaxis cannot find a quick route to...

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Trace.Space, a startup that uses AI to accelerate product design, raises...

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Evaluating Enterprise-Grade AI Assistants: A Benchmark for Complex, Voice-Driven Workflows

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This AI Paper Introduces Group Think: A Token-Level Multi-Agent Reasoning Paradigm...

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A Comprehensive Coding Guide to Crafting Advanced Round-Robin Multi-Agent Workflows with...

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Education

Optimizing Assembly Code with LLMs: Reinforcement Learning Outperforms Traditional Compilers

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AI Observer

Evaluating Enterprise-Grade AI Assistants: A Benchmark for Complex, Voice-Driven Workflows

As businesses increasingly integrate AI assistants, assessing how effectively these systems perform real-world tasks, particularly through voice-based interactions, is essential. Existing evaluation methods concentrate on broad conversational skills or limited, task-specific tool usage. However, these benchmarks fall short when measuring an AI agent’s ability to manage complex, specialized workflows...