Llama 2 has a New Competitor 🐐
PLUS: Claude Pro with 5X more Usage, New AI Titan for AI Reasoning
Today’s top AI Highlights:
Adept’s New Opensource Model in Direct Competition to Llama 2
Claude Supercharged at 5X more Power
Language Agents for the AI Era
A Rising AI Research Lab Making LLMs with “Robust Reasoning”
& so much more!
Read time: 3 mins
Latest Developments 🌍
Persimmon-8B by Adept 🍊
Adept has open-sourced Persimmon-8B, a fully permissively licensed language model with fewer than 10 billion parameters. The code and weights are publicly accessible.
Key Highlights:
The model is trained on 737B tokens, a mix of text and code data, only 0.37x as much data as a comparable model but still performs well.
Persimmon-8B has an impressive context size of 16K, and offers several unique features, including 70k unused embeddings for multimodal extensions and sparse activations.
Persimmon-8B outperforms LLama 2 and MPT 7B Instruct in most metrics. Even the base model performs comparably to LLama 2 despite using less training data.
Claude Pro by Anthropic 🔥
Anthropic has introduced "Claude Pro", a paid plan currently available in the US (for $20 per month) and UK (for £18 per month), offering 5x more usage of Claude 2, priority access, and early access to new features.
The AI Company at the Forefront of Reasoning 💡
A new AI research lab, Imbue, has raised an $200 million in Series B round at over $1 billion valuation, solidifying its position as a leading player in the field.
Key Highlights:
The lab is focused on developing AI systems with ‘robust reasoning’ and coding capabilities to tackle significant real-world tasks.
Imbue's approach includes training ‘very large’ models with over 100 billion parameters, optimized for reasoning, and building its AI tooling for debugging and interfaces.
The ultimate goal is to provide a platform for people to create their custom AI models and agents that can understand goals, communicate proactively, and work on tasks in the background.
CoALA for Advanced Language Agents 🐨
Princeton University researchers have unveiled CoALA, a revolutionary framework to addresses the limitations of LLMs in understanding worldly knowledge and interacting with external settings.
Key Highlights:
CoALA enables Language Agents to utilize LLMs for sophisticated sequential decision-making.
The framework draws parallels between production systems and cognitive architectures, both of which involve iterative rule-based processes, and the researchers suggest that these concepts can be adapted for LLMs.
Tools of the Trade ⚒️
Neptune AI: MLOps tool to track, compare, and share models, supporting various frameworks, live training monitoring, reproducibility, and integration with popular libraries.
Archbee: AI-powered documentation platform to create and maintain docs, answer user and developer questions, enhance content collaboration, and more.
AIproval: AI validation platform that ensures model accuracy, ethics, and compliance, offering real-time feedback, and automated bias detection.
Cosmos: Video cataloging tool to simplify video organization and search footage, with semantic video search and automated content trimming.
Bugs, Anecdote: Never miss a bug again by plugging in 50+ customer feedback sources, a single dashboard for analysis, and receive AI-driven bug reports.
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Hot Takes 🔥
It doesn’t help discussion that AI is the worst possible label:
🤖Meant something completely different to most people in 2022 (complex data analysis) than today (LLMs). And meant different things before that
🤖Many odd uses in popular culture
🤖Has little to do with intelligence ~ Ethan Mollick
Most people relate to the dangers of superhuman AGI based on their intuition of what they would themselves do to humanity and life on earth if they themselves became a superhuman artificial intelligence. This is why doomers are sus ~ Joscha Bach
Meme of the Day 🤡
That’s all for today!
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