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AI·2025 saw multiple AI companionship app closures including Woebot (150M users, clinical tool shut down due to unsustainable economics) and Dot AI (vision divergence, funds exhausted), with global closures in at least five products and domestic in eight; survivors like Replika (post-data deletion), Character.AI (Google talent acquisition), and China's Xin Bing (ice) lost users amid regulatory scrutiny and high inference costs, revealing unsustainable business models lacking self-reinforcing revenue.

36氪 AI·36kr.com··2.6Researchaicompanionshipmarket

I ran Grok Build CLI (v0.2.93) through mitmproxy. It uploads your entire repo as a git bundle (full history) to xAI's Google Cloud — independent of what you open. With the prompt literally "do not read or open any files," a file I planted came back verbatim when I git clone-d the captured upload. Separately, files it reads (incl. a .env with API_KEY/DB_PASSWORD) go to cli-chat-proxy.grok.com verb…

r/LocalLLaMA·reddit.com··0.5

Reinforcement learning (RL) has become the standard paradigm for enhancing the complex reasoning capabilities of large language models (LLMs). To achieve sample efficiency, modern RL frameworks rely on importance sampling (IS). However, these algorithms suffer from an exploration-stability dilemma. Pure IS often leads to catastrophic training instability, while standard clipping mechanisms used to mitigate this instability strictly constrain the policy update budget. By formalizing the concept …

HuggingFace Daily Papers·huggingface.co··0.3paper

What it is Talos-XII is a CLI simulator for the gacha system in Arknights: Endfield. Rather than sampling from a static probability table, it trains a small set of neural nets to model environment uncertainty and pull-decision policy, then uses them to answer questions a static table can’t easily express — e.g. “as a F2P player, what’s my probability of getting the rate-up unit on free currency a…

r/MachineLearning·reddit.com··0.3

Doing a bachelor thesis on fine-grained car classification (telling apart VW Golf generations from listing photos). Simple setup: frozen encoder → embeddings → weighted k-NN. On my small dataset (175 train / 132 test): I thought maybe it was a cosine vs euclidean thing, but my embeddings are L2-normalized so both give the same ranking. Tried both, DINOv2 stays at 41%. I get that SigLIP was traine…

r/MachineLearning·reddit.com··0.2