We can’t help treating AI like it’s human. But should we?
TechCrunch 5 days ago 27
MIT researchers and an author argue that people naturally anthropomorphize AI and robots, which can shape how they trust and emotionally rely on chatbots.
175 summarised stories about Language Models, each linking back to the original source. Browse all topics →
TechCrunch 5 days ago 27
MIT researchers and an author argue that people naturally anthropomorphize AI and robots, which can shape how they trust and emotionally rely on chatbots.
MarkTechPost 5 days ago 41
Underdog released Saluki 27B, a 2-bit GGUF version of Qwen3.8-27B designed for on-device agent tool calling under an Apache 2.0 license. It shrinks storage to 7.89 GB versus 54 GB for the full BF16 model while reporting 42 versus 35 parallel tool calls. The compression targets tool-use performance, so tool-calling improves relative to the full model while math and multi-step reasoning drop by about 12 to 18 points.
Simon Willison’s Weblog 6 days ago 44 ● 2 sources
ttok 1.0 was released after the author found the tool was defaulting to the GPT-4 tokenizer instead of the intended GPT-5/GPT-6 tokenizer, and used a tokenizer check to justify changing the default. The release cites a test where all seven GPT models produced 44,794 tokens across 31 fixtures, with GPT-6 showing no input-count change on that corpus. Tokenization defaults are updated so new runs use the GPT-5/GPT-6 family tokenizer rather than GPT-4.
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Sakana AI added a new transparency layer to Sakana Chat with “My Fish,” letting users see what the chatbot remembers, when those memories get used, and how related facts connect. The interface surfaces memory activity as small “chips” during responses and backs it up with a heatmap of memory use plus read/write history and a connection map. It’s a practical answer to a familiar problem: people don’t just want outputs from AI systems, they want a way to audit what the system is carrying forward.
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