EthixU is pioneering the future of ethical AI development through targeted education and community building. Our mission: “AI Learning Done Right.” We focus on shaping the minds that will create tomorrow’s AI technologies. By engaging directly with AI startup founders, students, professors and thought leaders, we’re building a foundation for ethical AI development. Our platform…
AWS DeepRacer League 2024 Championship finalists at re:Invent 2024 The AWS DeepRacer League is the world’s first global autonomous racing league powered by machine learning (ML). Over the past 6 years, a diverse community of over 560,000 builders from more than 150 countries worldwide have participated in the League to learn ML fundamentals hands-on through…
This post was written by Claudiu Bota, Oleg Yurchenko, and Vladyslav Melnyk of AWS Partner Automat-it. As organizations adopt AI and machine learning (ML), they’re using these technologies to improve processes and enhance products. AI use cases include video analytics, market predictions, fraud detection, and natural language processing, all relying on models that analyze data…
Organizations across many industries are harnessing the power of foundation models (FMs) and large language models (LLMs) to build generative AI applications to deliver new customer experiences, boost employee productivity, and drive innovation. Amazon Bedrock, a fully managed service that offers a choice of high-performing FMs from leading AI companies, provides the easiest way to…
Amazon Q Business is a fully managed, generative AI–powered assistant that empowers enterprises to unlock the full potential of their data and organizational knowledge. With Amazon Q Business, you can quickly access answers to questions, generate summaries and content, and complete tasks by using the expertise and information stored across various data sources and enterprise…
My name is Akash, co-founder and CEO of Bellum.ai. Our mission is to help companies build reliable AI systems in production. In this talk, I’ll share insights from working with hundreds of companies using AI, highlighting what works, what doesn’t, and where AI development is headed. The journey to AI innovation Early experiences with AI…
The following is a joint announcement from the MIT Microsystems Technology Laboratories and GlobalFoundries. MIT and GlobalFoundries (GF), a leading manufacturer of essential semiconductors, have announced a new research agreement to jointly pursue advancements and innovations for enhancing the performance and efficiency of critical semiconductor technologies. The collaboration will be led by MIT’s Microsystems Technology Laboratories (MTL)…
Introduction: The quest for reliable qubits Quantum computing faces a fundamental challenge: qubits, the basic units of quantum information, are notoriously fragile. Conventional approaches, such as superconducting circuits and trapped ions, require intricate error-correction techniques to counteract decoherence. Microsoft has pursued an alternative path: Majorana-based topological qubits, which promise inherent noise resistance due to their…
A vast search of natural diversity has led scientists at MIT’s McGovern Institute for Brain Research and the Broad Institute of MIT and Harvard to uncover ancient systems with potential to expand the genome editing toolbox. These systems, which the researchers call TIGR (Tandem Interspaced Guide RNA) systems, use RNA to guide them to specific…
This post is in six parts; they are: • Traditional vs Neural Approaches • Auto-Complete Architecture • Basic Auto-Complete Implementation • Caching and Batched Input When you type in a word in Google’s search bar, such as “machine”, you may find some additional words are suggested, such as “learning,” to make up “machine learning”.
In our previous blog posts, we explored various techniques such as fine-tuning large language models (LLMs), prompt engineering, and Retrieval Augmented Generation (RAG) using Amazon Bedrock to generate impressions from the findings section in radiology reports using generative AI. Part 1 focused on model fine-tuning. Part 2 introduced RAG, which combines LLMs with external knowledge…
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