Observed Signal · Apr 25, 2024 · Technical Release · Source: Trending Topics · Impact: 4/5 · Sentiment: Positive
Apple Releases 8 New Open-Source AI Models with OpenELM
Apple has introduced OpenELM, a family of eight open-source language models designed to run directly on-device rather than on cloud servers. Four models were pre-trained using Apple's newly launched CoreNet library, while the other four are instruction-tuned models. The models, training protocols, and evaluation framework are publicly available via Hugging Face Hub. Apple says the release aims to support the open research community and reduce risks and biases in AI. The company is pursuing a layer-wise scaling strategy to improve LLM accuracy and efficiency. Apple CEO Tim Cook has previously stated generative AI features will arrive on Apple devices this year. Bloomberg's Mark Gurman reports iOS 18 will rely on a large on-device language model, which could improve privacy and speed. Apple is expected to unveil iOS 18 at WWDC on June 10.
Apple, a major platform, releases open-source on-device LLMs, advancing mobile AI capabilities and privacy-preserving AI, which will influence the app ecosystem and AI-related advertising technologies.
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Key Takeaways & Evidence Grounding
- Apple released eight OpenELM open-source language models on April 25, 2024.
- The models run directly on-device, not on cloud servers.
- Four models were pre-trained with Apple's new CoreNet library; four are instruction-tuned.
- The training and evaluation framework is available via Hugging Face Hub.
- Bloomberg's Mark Gurman reports iOS 18 will mainly use an on-device language model.
Connected Companies & Entities
3 Entities mapped“Apple hat heute acht Open Source Sprachmodelle vorgestellt, die OpenELM-Modelle....”
“Entwickler:innen können via Hugging Face, der Community für den Austausch von KI-Code, darauf zugreifen....”
“Laut Apple-Chefkorrespondent Mark Gurman von Bloomberg werden die KI-Funktionen in iOS 18 hauptsächlich von einem großen Sprachmodell direkt...”
Ontology Mapping & Concepts
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Fired OpenAI Researchers Dispute Misconduct Claims, Warn of Chilling Effect
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Goodfire Launches Internal AI Agent Monitors
Goodfire, a startup specializing in AI interpretability, launched on Thursday a new type of AI agent monitor that inspects a model's internal signals rather than reading its output, aiming to detect rogue behaviors more efficiently and at a fraction of the cost. The monitors are available to customers of Baseten, an AI model hosting platform. Baseten's Base Labs had previously announced a safety partnership with Goodfire and Hugging Face. Goodfire's approach uses small probes that scan a model's internal activations at each step, triggering a closer AI review only when flagged. In tests on the Kimi K3 model, Goodfire's monitors caught 94% of malicious hacking sessions and cost about $51 for 1,500 sessions, compared to $233 for a cheaper model and $10,000 for a top-tier one. The company positions the solution for open models, which can be stripped of safeguards, and sees it as critical for inference-time guardrails.
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