MIT researchers developed a system using large language models to convert complex AI explanations into plain language, improving user understanding. The system evaluates the quality of the narrative, allowing users to trust machine-learning predictions and customize explanations to meet specific needs.
Pixtral 12B, Mistral AI's cutting-edge vision language model, excels in text-only and multimodal tasks, outperforming other models. It features a novel architecture with a 400-million-parameter vision encoder and a 12-billion-parameter transformer decoder, offering high performance and speed for understanding images and documents.
Australian federal police relies on AI for investigations due to vast data volume. 40 terabytes of data analyzed on average, with a cyber incident reported every 6 minutes.
OpenAI's new tool, Sora, creates realistic video clips from prompts, raising concerns about the blurring line between reality and AI-generated content. Despite impressive visuals, witnessing the uncanny realism left the journalist feeling more melancholic than amazed.
Classification models provide not only answers but also confidence levels through probability scores. Explore how seven basic classifiers calculate and express their prediction certainty visually. Understanding predicted probability is key to interpreting how models make choices with varying levels of confidence.
MIT's Daniela Rus receives 2024 John Scott Award for groundbreaking robotics research, redefining the capabilities of robots beyond traditional norms. Rus's work focuses on developing explainable algorithms to create collaborative robots that can solve real-world challenges, emphasizing the synergy between the body and brain for intelligent machines.
MIT researchers developed a new technique to improve machine-learning model accuracy for underrepresented groups by removing specific data points. This method addresses hidden biases in training datasets, ensuring fair predictions for all individuals.
Summary: Learn three zero-cost solutions to improve data quality efficiently. Utilize old-school database tricks, create custom dashboards, and generate data lineage with Python. Simplify processes and reduce complexity for better data quality outcomes.
Large language models like ChatGPT are advancing rapidly but may exhibit political bias. MIT study questions if reward models can be both truthful and unbiased.
Two approaches to gain insights on multimodal data: embed first, infer later with Amazon Titan Multimodal Embeddings, and infer first, embed later with Anthropic’s Claude 3 Sonnet. Evaluation using SlideVQA dataset, providing concise responses to user questions.
Paul McCartney warns AI could threaten income streams for creators, calls for laws against mass copyright theft by AI companies. The former Beatle expresses concern over young composers and writers unable to protect their intellectual property from algorithmic models.
Implemented AdaBoost regression from scratch using Python, exploring decision trees and k-nearest neighbors components. Found original source paper for AdaBoost. R2 algorithm, facing challenging but rewarding engineering process.
Southeast Asia embraces sovereign AI with Thailand and Vietnam PMs meeting NVIDIA CEO. NVIDIA announces collaboration with Vietnam gov't and acquisition of VinBrain.
Elon Musk, known for his interests in EVs and space travel, now eyes British politics. Reportedly set to make a historic £80m donation to Nigel Farage's Reform UK party.
Implementing Speculative and Contrastive Decoding enhances text generation quality and efficiency using large and small language models. Contrastive Decoding prioritizes tokens with the largest probability difference between models for high-quality outputs.