Google DeepMind Scientist Says AI Will Never Be Conscious, No Matter How Powerful—Here's Why
Google DeepMind 科學家爆料:AI 永遠不會有意識,再等 100 年也沒用——他說這叫「抽象謬誤」
Alexander Lerchner, a senior scientist at Google DeepMind, is pushing back hard against the idea that we'll ever create conscious AI, even if we wait 100 years. He calls the whole thing the 'Abstraction Fallacy'—basically, people assume that because AI can process information and seem intelligent, it must eventually become conscious. But Lerchner argues that's a fundamental misunderstanding of how these systems actually work. It's a pretty bold take in a field where everyone's obsessed with scaling up models bigger and bigger, assuming consciousness will just... happen eventually. Worth reading if you're tired of the hype around AI becoming sentient.
OpenAI is hosting a livestream event. Details about the specific announcements, product launches, or demonstrations will be revealed during the broadcast.
The last time OpenAI did an unannounced livestream, they dropped GPT-4 Turbo and changed pricing overnight
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ChatGPT Images 2.0
OpenAI is launching ChatGPT Images 2.0 with major upgrades to image generation capabilities. Watch the livestream announcement at https://openai.com/live/
OpenAI is positioning this as a direct competitor to established image generation tools, suggesting they're confident enough to challenge the current market leaders
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The "just wait 6 months" argument from 2025 survived exactly one iteration
Throughout 2025 the standard response to any complaint about an LLM was some version of "just wait 3-6 months, the next generation will handle this effortlessly." The argument was everywhere. Every limitation was temporary, every missing capability was a few iterations away, every autonomous agent demo was a preview of imminent reality.
It's April 2026 now and worth checking how that held up.
On r/ClaudeAI this week there's a long thread about Opus 4.7 where multiple users argue it's a regress
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Mistral Medium 3.5 on AMD Strix Halo: Painfully Slow (Plan for Overnight Runs)
Someone actually tested Mistral Medium 3.5 on AMD's new Strix Halo chip, and the results are... not great. For a 48k-token prompt with 4k thinking tokens, it took about 2 hours just to get an answer about code architecture. Yeah, you read that right—two hours. The takeaway: if you want to run this locally on Strix Halo, queue it up before bed. The technical setup involved heavy optimization (Q5_K_XL quantization, GPU acceleration with -ngl 999, cache reuse), but even with all that tuning, it's still a crawl. Not exactly the "instant local AI" dream, but hey, at least it works.