NEWS IN BRIEF: AI/ML FRESH UPDATES

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DIY Dataset: LLM Training 101

Large language models (LLMs) require well-curated datasets for optimal performance. Data preprocessing involves extracting text from diverse sources and filtering for quality, using tools like OCR and regex filters.

MIT Welcomes Frida Polli: Visiting Innovation Scholar

Frida Polli, MIT's new visiting innovation scholar, transitioned from neuroscience to entrepreneurship, co-founding successful AI company pymetrics. Polli's work led to algorithmic bias law, collaboration with Sendhil Mullainathan to bridge behavioral science and computer science at MIT.

Master AdaBoost Regression in C#

AdaBoost.R2 modifies AdaBoost for regression, creating a sequence of decision trees for better predictions. Weighted median enhances accuracy by emphasizing high-confidence tree predictions.

AI Decodes Whisky Aromas

Artificial intelligence outperforms experts in identifying whisky notes. AI predicts aromas and origin accurately, advancing automated whisky aroma analysis.

Mastering Soft Actor-Critic RL

Soft Actor-Critic (SAC) is a new off-policy deep RL algorithm addressing stability issues in high-dimensional environments. SAC promotes robustness and exploration in bioengineering systems like de novo drug design.

UK Technology Access for Blacklisted Chinese AI Chip Firms

Imagination Technologies licenses UK tech to Chinese firms for AI chips in advanced weapons systems, raising national security concerns. Chinese companies Moore Threads and Biren Technology under US export restrictions for developing AI chips for military purposes.

MIT engineers reach new heights with 3D chip growth

Chip manufacturers are exploring multilayered chip designs to increase computing power. MIT engineers have developed a method to stack high-quality semiconducting layers without bulky silicon substrates, potentially revolutionizing AI hardware.

Revolutionizing LLM Safety: NeurIPS 2024 Challenge Insights

NeurIPS 2024 Challenge 2nd prize winner presents a unique approach to effective LLM unlearning without retaining dataset, using reinforcement learning and classifier-free guidance. The competition focused on forcing LLM to generate personal data and protecting it; solution involved supervised finetuning, reinforcement learning, and CFG.

Streamlining AI with Amazon Bedrock Automation

Amazon Bedrock Data Automation simplifies data extraction from unstructured assets, offering a unified experience for developers to automate insights from documents, images, audio, and videos. Customers can easily generate standard or custom outputs, integrating Amazon Bedrock Data Automation into existing applications for efficient media analysis and intelligent document processing workflows.