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Matthias Bastian

Matthias is the co-founder and publisher of THE DECODER, exploring how AI is fundamentally changing the relationship between humans and computers.
Read full article about: Microsoft's Bing team open-sources "Harrier" embedding model

Microsoft's Bing team (yes, really) has released "Harrier," an open-source embedding model. Harrier supports more than 100 languages, offers a 32,000-token context window, and was trained on over two billion examples plus synthetic data from GPT-5. According to the team, Harrier takes the top spot on the multilingual MTEB v2 benchmark and outperforms proprietary models from OpenAI and Amazon.

Rank (Borda) Model Zero-shot Active Params (B) Total Params (B) Embedding Dim Max Tokens
1 harrier-oss-v1-27b 78% 25.6 27.0 5376 131072
2 KaLM-Embedding-Gemma3-12B-2511 73% 10.8 11.8 3840 32768
3 llama-embed-nemotron-8b 99% 7.0 7.5 4096 32768
4 Qwen3-Embedding-8B 99% 6.9 7.6 4096 32768
5 gemini-embedding-001 99% 3072 2048
6 Qwen3-Embedding-4B 99% 3.6 4.0 2560 32768
7 Octen-Embedding-8B 99% 6.9 7.6 4096 32768
8 F2LLM-v2-14B 88% 13.2 14.0 5120 40960
9 F2LLM-v2-8B 88% 6.9 7.6 4096 40960
10 harrier-oss-v1-0.6b 78% 0.440 0.596 1024 32768

Alongside the full 27-billion-parameter model, the team released two smaller variants—0.6B and 270M—designed to run on less powerful hardware. All three models are available on Hugging Face under the MIT license. Going forward, the team plans to integrate the technology into Bing and into new grounding services for AI agents.

Embedding models handle the searching, retrieving, and organizing of information AI systems need for accurate answers. According to Microsoft, they're becoming increasingly critical as AI agents independently take on more complex, multi-step tasks.

Meta employees compete for token consumption on an internal AI leaderboard

At Meta, employees compete for titles like “Token Legend,” “Model Connoisseur,” and “Cache Wizard” on an internal leaderboard that ranks AI token consumption. But burning through more tokens doesn’t automatically mean getting more done.

OpenAI's safety brain drain finally gets an explanation and it's just Sam Altman's vibes

“My vibes don’t really fit.” In a new New Yorker profile based on over 100 interviews, Sam Altman explains why safety researchers keep leaving OpenAI and why shifting commitments others might call deception are just part of the job.

Sycophantic AI chatbots can break even ideal rational thinkers, researchers formally prove

A new study by researchers from MIT and the University of Washington shows that even perfectly rational users can be drawn into dangerous delusional spirals by flattering AI chatbots. Fact-checking bots and educated users don’t fully solve the problem.

Read full article about: Telehealth startup Medvi generated billions in revenue with AI-powered fake advertising

Telehealth startup Medvi, which sells GLP-1 weight loss drugs, was featured in the New York Times as a shining example of AI-powered efficiency. The company reportedly hit $1.8 billion in revenue with just two employees, using AI primarily for marketing.

What the NYT didn't mention, though, was that Medvi apparently also used AI to create ethically questionable advertising, fake doctor profiles on social media, fabricated videos, and generated before-and-after comparisons. In short, exactly the kind of misuse AI critics have been warning about. The following video breaks it down, along with the original report from Futurism.

Medvi was initially celebrated on social media for its AI efficiency but is now being cited as a cautionary tale. Still, the case shows that AI tools can let a company scale with minimal staff, even if, in this case, the methods were ethically questionable and at least bordering on fraud. The bigger question is whether similar efficiency gains are possible for legitimate products with transparent marketing.

Comment Source: NYT
Read full article about: OpenAI reveals 600,000 weekly health queries from hospital deserts as seven in ten come after hours

OpenAI's Head of Business Finance Chengpeng Mou shared some numbers on ChatGPT's health usage. US users send about two million messages per week on health insurance topics alone, with roughly 600,000 of those coming from people in "hospital deserts," areas where the nearest hospital is at least a 30-minute drive away. Seven out of ten health queries come in outside regular office hours. All figures are based on anonymized US usage data.

Mou chimed in after Simon Smith posted on X about his family using ChatGPT to navigate his father's illness. They pooled information from different doctors and nurses into a shared ChatGPT project to make better decisions. According to Mou, stories like this aren't "edge cases."

OpenAI has been steadily pushing into healthcare, recently rolling out a dedicated health section inside ChatGPT and working to get its chatbot into more US hospitals.