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Apple Announces MM1: A Family of Multimodal LLMs Up To 30B Parameters that are SoTA in Pre-Training Metrics and Perform Competitively after Fine-Tuning

Recent research has focused on crafting advanced Multimodal Large Language Models (MLLMs) that seamlessly integrate visual and textual data complexities. By delving into the minutiae of architectural design, data selection, and methodological transparency, research has pushed the boundaries of what MLLMs can achieve and support future explorations. Their work is particularly notable for its comprehensive approach to dissecting the various components that contribute to the success of these models, shedding light on the pivotal roles played by image encoders, vision-language connectors, and the strategic amalgamation of diverse data types. The researchers at Apple build MM1, a family of cutting-edge multimodal

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Mind blowing stuff by Claude 3, even it's basic version is somehow close to GPT-4 🔥 And Claude 3 OPUS is surpassing everyone in all criterias 🔥😀
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Every LLM has a personality GPT-4 is like a lazy reticent teenager refusing to answer questions, requiring a lot of pushing to write code and do things Claude 3 is like an eager and thoughtful adult with a bias for action Gemini is a holier-than-thou wokist that strives too hard to be politically correct - Source Twitter
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Tensorflow 2.16 is here : https://goo.gle/3TyyA6p
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What's new in TensorFlow 2.16

TensorFlow 2.16 has been released! Highlights include Clang as default compiler for building TensorFlow CPU wheels on Windows, and more.

BREAKING: The European Parliament has just APPROVED the AI Act. What everyone should know: ➵ The AI Act follows a risk-based approach. Some AI systems are banned, such as those involving: - Cognitive behavioral manipulation of people or specific vulnerable groups; - Social scoring: classifying people based on behavior, socioeconomic status, or personal characteristics; - Biometric identification and categorization of people; - Real-time and remote biometric identification systems, such as facial recognition. Some AI systems fall in the "high-risk" category, such as those involving: - Critical infrastructures (e.g. transport) that could put the life and health of citizens at risk; - Educational or vocational training that may determine the access to education and professional course of someone’s life (e.g. scoring of exams); - Safety components of products (e.g. AI application in robot-assisted surgery); - Employment, management of workers, and access to self-employment (e.g. CV-sorting software for recruitment procedures); - Essential private and public services (e.g. credit scoring denying citizens opportunity to obtain a loan); law enforcement that may interfere with people’s fundamental rights (e.g. evaluation of the reliability of evidence); - Migration, asylum, and border control management (e.g. automated examination of visa applications); - Administration of justice and democratic processes (e.g. AI solutions to search for court rulings). ➵ High-risk AI systems will be assessed before being put on the market and also throughout their lifecycle. People will have the right to file complaints about AI systems to designated national authorities. ➵ Generative AI, like ChatGPT, will not be classified as high-risk but will have to comply with transparency requirements and EU copyright law. Some of the obligations are: - Disclosing that the content was generated by AI; - Designing the model to prevent it from generating illegal content; - Publishing summaries of copyrighted data used for training. The AI Act is expected to officially become law by May or June, and its provisions will start taking effect in stages: - 6 months later: countries will be required to ban prohibited AI systems; - 1 year later: rules for general-purpose AI systems will start applying; - 2 years later: the whole AI Act will be enforceable. ➵ Fines for non-compliance can be up to 35 million Euros or 7% of worldwide annual turnover.
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