The author employed AI to enhance the performance of their existing C# gradient boosting regression implementation, resulting in significant improvements. Gradient boosting regression is a tree-based method used to predict a single numeric value, such as predicting a maximum safe loan amount based on various factors. This process involves creating a collection of decision trees, where each tree...
This text discusses the benefits and evolution of enterprise agentic retrieval using Amazon Bedrock Knowledge Bases on the AWS Cloud Development Kit (CDK). Traditional Retrieval Augmented Generation (RAG) systems have limitations, such as handling questions that span multiple corpora or require multiple lookups. To overcome these challenges, the text introduces agentic retrieval, where a reason...
Climate Week NYC, an annual event bringing together over 100,000 people in more than 1,000 events across New York City to discuss climate challenges and explore solutions, saw a strong presence from the MIT community this year. MIT was represented multiple days with appearances by Evelyn Wang, vice president for energy and climate, and numerous sessions organized by MIT departments, labs, cente...
This text discusses the challenge of managing computer vision models across multiple cameras in industrial quality inspection systems. Each camera captures the world differently, resulting in unique training data. To address this, individual fine-tuned models are needed for each camera, leading to the need to train, evaluate, version, and ship thousands of models without human intervention. The...
Amazon Quick Sight's geospatial maps allow businesses to visualize patterns connected to location through point maps, filled maps, and now, layer maps. With the new point and LineString geometry types from GeoJSON files, users can mark specific locations and trace routes. This post covers dataset and GeoJSON structure, prerequisites, and advanced techniques for creating layer maps in Amazon Qui...
In the early development of artificial intelligence (AI), engineers like those at MIT believed introducing randomness and irrationality were necessary for machines to mimic human-like creativity, according to MIT assistant professor Benjamin Lindquist. Tracing back to mid-20th century ideas, engineers saw creativity as stemming from unexpected leaps of logic or even a dream-like state. To emula...
Multi-Turn Reinforcement Learning (MTRL) is a training method used to teach models to complete multi-step tasks with feedback only after the entire sequence. In contrast to fine-tuning, MTRL doesn't rely on a single correct sequence or label. Agents interact with an environment, making decisions, and reporting rewards after each sequence ends. With MTRL, a model can be made proficient in a spec...
NVIDIA founder and CEO Jensen Huang recently visited Astana, Kazakhstan, where he discussed the country's push to build a strong ecosystem for artificial intelligence (AI). Kazakhstan's goal is to create AI that reflects its language and culture, utilizing its abundant energy resources to support homegrown AI and transforming energy into intelligence for export. The conversation also touched on...
MIT's School of Humanities, Arts, and Social Sciences was celebrated at its 75th Anniversary Symposium for its value and contributions to teaching, research, and society. The event, held at the Linde Music Building, drew scholars, students, staff, and alumni from across the school. MIT leadership, including President Sally Kornbluth and Provost Anantha Chandrakasan, emphasized the importance of...
Bayer Crop Science uses machine learning models to analyze data from genomics, field trials, imagery, and environmental conditions for plant breeding. To manage and make repeatable and governable these ML model configurations, Bayer developed the Connected Decision Engine (CDE). As the usage increased, understanding the results became a challenge, leading to the creation of the Agentic Decision...
When updating Amazon SageMaker AI real-time endpoint configuration, changing the instance type, instance count, or environment variables through AWS CloudFormation or AWS CDK can result in deployment failure. This is due to SageMaker AI requiring the scalable target to be deregistered before updating the endpoint. However, deregistering the scalable target causes CloudFormation to lose track of...
IskayPet, a leading pet care company in Iberia with operations in Spain, Portugal, and France, faced a challenge in efficiently answering operational questions across retail, veterinary care, animal care, procurement, and people and onboarding, spread across hundreds of Microsoft SharePoint documents in four languages. The time-consuming process of manually searching and verifying information l...
This article discusses a solution to improve the response time of AI voice agents by closing the gap between generation and synthesis of text-to-speech (TTS) responses. Instead of waiting for the full response to be generated before starting synthesis, each sentence generated by an agent is immediately streamed to a hosted TTS model on Amazon SageMaker AI, allowing audio playback to begin befor...
In this text, the author describes their experience using random forest regression, specifically with Extra Trees learners, compared to the standard architecture. The goal is to predict a single numeric value using various regression techniques, with tree-based methods being one category. Random forest regression uses multiple decision trees with different subsets of the data, averaging the res...
Rescale's AI-driven platform accelerates innovation in engineering by integrating HPC, modeling, simulation, and AI. They used AI-DLC on AWS to build an intelligent triage agent, reducing operational overhead and speeding up deployment.