Artificial Intelligence (AI)
Ray Kurzweil ’70 reinforces his optimism in tech progress
Innovator, futurist, and author Ray Kurzweil ’70 emphasized his optimism about artificial intelligence, and technological progress generally, in a lecture on Wednesday while accepting MIT’s Robert A. Muh Alumni Award from the School of Humanities, Arts, and Social Sciences (SHASS). Kurzweil offered his signature high-profile forecasts about how AI and computing will entirely blend with human…
Liquid AI Releases LFM2-8B-A1B: An On-Device Mixture-of-Experts with 8.3B Params and a 1.5B Active Params per Token
How much capability can a sparse 8.3B-parameter MoE with a ~1.5B active path deliver on your phone without blowing latency or memory? Liquid AI has released LFM2-8B-A1B, a small-scale Mixture-of-Experts (MoE) model built for on-device execution under tight memory, latency, and energy budgets. Unlike most MoE work optimized for cloud batch serving, LFM2-8B-A1B targets phones,…
What It Really Takes to Fine-Tune a LLM Model for a Real-World Use Case
Imagine you’re leading an AI initiative at a mid-sized healthcare startup. Your team has prototyped a patient-facing chatbot that helps summarize diagnoses and explain treatment options using a large language model. The demo went well — the investors are thrilled, and leadership wants it in production. But one week into “real-world testing,” you’re staring at…
Using generative AI to diversify virtual training grounds for robots
Chatbots like ChatGPT and Claude have experienced a meteoric rise in usage over the past three years because they can help you with a wide range of tasks. Whether you’re writing Shakespearean sonnets, debugging code, or need an answer to an obscure trivia question, artificial intelligence systems seem to have you covered. The source of…
An Intelligent Conversational Machine Learning Pipeline Integrating LangChain Agents and XGBoost for Automated Data Science Workflows
In this tutorial, we combine the analytical power of XGBoost with the conversational intelligence of LangChain. We build an end-to-end pipeline that can generate synthetic datasets, train an XGBoost model, evaluate its performance, and visualize key insights, all orchestrated through modular LangChain tools. By doing this, we demonstrate how conversational AI can interact seamlessly with…
Printable aluminum alloy sets strength records, may enable lighter aircraft parts
MIT engineers have developed a printable aluminum alloy that can withstand high temperatures and is five times stronger than traditionally manufactured aluminum. The new printable metal is made from a mix of aluminum and other elements that the team identified using a combination of simulations and machine learning, which significantly pruned the number of possible…
Building a Human Handoff Interface for AI-Powered Insurance Agent Using Parlant and Streamlit
Human handoff is a key component of customer service automation—it ensures that when AI reaches its limits, a skilled human can seamlessly take over. In this tutorial, we’ll implement a human handoff system for an AI-powered insurance agent using Parlant. You’ll learn how to create a Streamlit-based interface that allows a human operator (Tier 2)…
Why No-Code AI Builders (Like Lovable or Bolt) Still Need Dev Partners to Truly Work – Spritle software
The Friday Night Dream It’s Friday night. You’ve got takeout on the table, your laptop open and an idea you’ve been carrying around for months.You sign up for Lovable — the “world’s first AI full-stack engineer.” You type in:“Build me a full-stack e-commerce app with login, product pages, shopping cart, and Stripe checkout.” The screen…
Google DeepMind introduces new AI agent for code security
Responsibility & Safety Published 6 October 2025 Authors Raluca Ada Popa and Four Flynn Using advanced AI to fix critical software vulnerabilities Today, we’re sharing early results from our research on CodeMender, a new AI-powered agent that improves code security automatically. Software vulnerabilities are notoriously difficult and time-consuming for developers to find and fix, even…
How to Evaluate Voice Agents in 2025: Beyond Automatic Speech Recognition (ASR) and Word Error Rate (WER) to Task Success, Barge-In, and Hallucination-Under-Noise
Optimizing only for Automatic Speech Recognition (ASR) and Word Error Rate (WER) is insufficient for modern, interactive voice agents. Robust evaluation must measure end-to-end task success, barge-in behavior and latency, and hallucination-under-noise—alongside ASR, safety, and instruction following. VoiceBench offers a multi-facet speech-interaction benchmark across general knowledge, instruction following, safety, and robustness to speaker/environment/content variations, but…