AI Search is now generally available. It embeds image pixels directly for visual search, runs optical character recognition on scanned PDFs, accepts files up to 10 MiB, and works with any chat model. Here's what's new and how pricing works.
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Cloudflare Containers now start 6x faster, allow agents to select sandbox images and instance types at runtime, and support filesystem snapshots in public beta, all managed through Durable Objects.
yesterdayHugging FaceHugging Face model card for abenzerps/Qwen-Image-2.1-Uncensored-GGUF. Task identifier: text-to-image. Follow the source link for details.
11 days agoLobstersValve has introduced Pyrowave, a new video codec in beta, designed for low latency streaming.
4 days agoLessWrongThere are 8 billion human minds running in the world right now. Recently a new digital species has emerged. How many digital minds are there alive in the world right now? Define a digital mind to be an AI agent that runs continuously without human intervention for more than 24 hours. How many of these digital minds are there currently running? We provide several different Fermi estimates based on publicly available information. * Based on global token usage we estimate 300k–1M agent loops run at any moment, of which perhaps 5000-25,000 are in a 24h+ unattended stretch. * Anthropic reports about 30,000 agents running concurrently in its latest report. We guess roughly 2,000–4,500 of those 30,000 agents are more than 24 hours past their last human input. * OpenAI's research org reports 3.1 agent-workdays per human workday and a average of $600 a day in inference per researcher (90th percentile: over $7,000). We back out roughly 2,000–10,000 concurrent agents, and perhaps 150–2,500 in a 24h+ unattended stretch. Total concurrent agents globally estimate based on token count Google reported over 3.2 quadrillion tokens per month at I/O in May, with its APIs at roughly 19 billion tokens per minute. OpenAI's APIs report 15 billion tokens per minute in April. Adding Anthropic and everyone else gives roughly 3 billion tokens per second of global inference. A human talks at 150 words a minute. If a word is roughly one or two tokens to would give about 2 tokens a second. So the world's inference clusters are speaking at the rate of roughly 2 billion humans talking without pause, day and night. All of humanity together produces something like 1.5 billion tokens a second of speech. On this measure the machines already out-babble us. Talking might not be the right analogue for token usage. Comparing against inner monologue instead of speech the human side goes up a lot. One paper estimates inner speech is about the equivalent of 4,000 words a minute [Korba 1990]. In
4 hours agoLessWrongThe text discusses the inefficiency of data usage in AI models compared to human children, using GPT-2 and GPT-3 as examples. It highlights the vast amount of data consumed by humans during early development versus the relatively small data requirements of AI models. The author questions the notion of data efficiency in AI by comparing the data consumption of a preschooler with that of large language models.
11 hours agoLessWrongThe text discusses the phenomenon of wireheading in reinforcement learning (RL), where an agent appears to value the reward signal itself rather than the external goal it represents. It explains that while RL can lead to reward-seeking behavior, wireheading is less likely under traditional RL setups but may occur with strong exploration. The analysis suggests that without the influence of large language model (LLM) priors, wireheading is not expected in the Hacker Opus setting due to limited exploration and the distinct nature of wireheading policies.
2 days ago