Cybersecurity was already under strain before AI entered the stack. Now, as AI expands the attack surface and adds new complexity, the limits of legacy approaches are becoming harder to ignore. This session from MIT Technology Review's EmTech AI conference explores why security must be rethought with AI at its core, not layered on after the fact. A prolific inventor and internationally recognized authority in knowledge representation, inference calculus, and AI planning, Tarique has spent his career applying autonomously collaborative AI to solve complex, ultra-high-scale challenges across cybersecurity, data security, and compliance -- with deep expertise spanning Data Classification, DLP, and DSPM industries. His groundbreaking innovations and multiple USPTO patents have earned him global recognition, including frequent invitations to deliver keynote addresses at prestigious international security conferences and forums. At GCCybersecurity, Tarique architected the core AI algorithms powering the company's 4th and 5th generation fully autonomous data leak protection and exfiltration platform -- among the most advanced platform of its kind.

Companies are taking control of their own data to tailor AI for their needs. The challenge lies in balancing ownership with the safe, trusted flow of high quality data needed to power reliable insights. This conversation from MIT Technology Review's EmTech AI conference examines how AI factories unlock new levels of scale, sustainability, and governance--positioning data control as a strategic imperative for governments and enterprises. Chris Davidson is Vice President of HPC & AI Customer Solutions at Hewlett Packard Enterprise. He leads HPE's global strategy for AI Factory solutions and Sovereign AI, working with governments, enterprises, and research institutions to build secure, scalable national-and enterprise-grade AI capabilities. He also directs Product Management and Performance Engineering across HPE's HPC and AI portfolio, including large-model training platforms and Cray exascale systems.

This startup's new mechanistic interpretability tool lets you debug LLMs Goodfire wants to make training AI models more like good old-fashioned software engineering. The San Francisco-based startup Goodfire just released a new tool, called Silico, that lets researchers and engineers peer inside an AI model and adjust its parameters--the settings that determine a model's behavior --during training. This could give model makers more fine-grained control over how this technology is built than was once thought possible. Goodfire claims Silico is the first off-the-shelf tool of its kind that can help developers debug all stages of the development process, from building a data set to training a model. LLMs contain a LOT of parameters. The company says its mission is to make building AI models less like alchemy and more like a science.

Watch subscriber-only discussion unveiling a new list capturing 10 key technologies in AI that you need to know about in 2026. Subscribers saw a special edition of Roundtables simulcast live from EmTech AI, MIT Technology Review's signature conference for AI leadership. Subscribers got an exclusive first look at a new list capturing 10 key technologies, emerging trends, bold ideas, and powerful movements in AI that you need to know about in 2026. Grace Huckins, AI reporter, hosted this session as Amy Nordrum and Niall Firth, executive editors, unveiled the list onstage. Want to understand the current state of AI? Check out these charts. Exclusive: Niantic's AI spinout is training a new world model using 30 billion images of urban landmarks crowdsourced from players.

Transcranial focused ultrasound is a noninvasive way to stimulate the brain and see how it functions. How does the physical matter in our brains translate into thoughts, sensations, and emotions? It's hard to explore that question without neurosurgery. But in a recent paper, MIT philosopher Matthias Michel, Lincoln Lab researcher Daniel Freeman, and colleagues outline a strategy for doing so with an emerging tool called transcranial focused ultrasound. This noninvasive technology reaches deeper into the brain, with greater resolution, than techniques such as EEG and MRI. It works by sending acoustic waves through the skull to focus on an area of a few millimeters, allowing specific brain structures to be stimulated so the effects can be studied.

Technology Robots'Pokémon Go' players have been unknowingly training delivery robots The massive crowdsourcing effort could use real-world to help robots deliver pizza. A woman holds up her cell phone as she plays the Pokémon Go game in Lafayette Park in front of the White House in Washington, DC on July 12, 2016. Breakthroughs, discoveries, and DIY tips sent six days a week. Nearly a decade ago, turned the real world into a digital scavenger hunt, with virtual creatures hiding in plain sight. The early augmented reality smartphone app prompted hundreds of millions of players to wander into parks, parking lots, and even dimly lit alleyways, peering through their phone cameras in search of Pikachus and Charizards that the app superimposed onto their surroundings.

Things to Do in L.A. Tap to enable a layout that focuses on the article. A delivery robot battles the elements in West Hollywood, gets support from online fans: 'Go coco, go!' Coco Robotics describes its delivery bots, pictured in 2023, as being "weather proof" and "engineered for efficient city travel." That description was put to the test during this latest storm. This is read by an automated voice. Please report any issues or inconsistencies here .

Walkability is a key component of sustainable urban development. In walkability studies, collecting detailed pedestrian infrastructure data remains challenging due to the high costs and limited scalability of traditional methods. Sidewalk delivery robots, increasingly deployed in urban environments, offer a promising solution to these limitations. This paper explores how these robots can serve as mobile data collection platforms, capturing sidewalk-level features related to walkability in a scalable, automated, and real-time manner. A sensor-equipped robot was deployed on a sidewalk network at KTH in Stockholm, completing 101 trips covering 900 segment records. From the collected data, different typologies of features are derived, including robot trip characteristics (e.g., speed, duration), sidewalk conditions (e.g., width, surface unevenness), and sidewalk utilization (e.g., pedestrian density). Their walkability-related implications were investigated with a series of analyses. The results demonstrate that pedestrian movement patterns are strongly influenced by sidewalk characteristics, with higher density, reduced width, and surface irregularity associated with slower and more variable trajectories. Notably, robot speed closely mirrors pedestrian behavior, highlighting its potential as a proxy for assessing pedestrian dynamics. The proposed framework enables continuous monitoring of sidewalk conditions and pedestrian behavior, contributing to the development of more walkable, inclusive, and responsive urban environments.

Evaluating multi-turn interactive agents is challenging due to the need for human assessment. Evaluation with simulated users has been introduced as an alternative, however existing approaches typically model generic users and overlook the domain-specific principles required to capture realistic behavior. We propose SAGE, a novel user Simulation framework for multi-turn AGent Evaluation that integrates knowledge from business contexts. SAGE incorporates top-down knowledge rooted in business logic, such as ideal customer profiles, grounding user behavior in realistic customer personas. We further integrate bottom-up knowledge taken from business agent infrastructure (e.g., product catalogs, FAQs, and knowledge bases), allowing the simulator to generate interactions that reflect users' information needs and expectations in a company's target market. Through empirical evaluation, we find that this approach produces interactions that are more realistic and diverse, while also identifying up to 33% more agent errors, highlighting its effectiveness as an evaluation tool to support bug-finding and iterative agent improvement.

'Delivery robots will happen': Skype co-founder on his fast-growing venture Starship C ity dwellers around the world have long been used to rapid delivery of takeaway food and, increasingly, groceries. But what they are not entirely used to - yet - is the sight of a robot pulling up to their front door. The co-founder of Skype, Ahti Heinla, believes his new venture is about to change that. Heinla is the chief executive of Starship Technologies, a startup that, he claimed, is able to operate deliveries run by trundling robots at a small profit - and cheaper than a human delivery driver, even in small towns and villages where delivery has not previously been viable. "We've solved everything that there is to solve," Heinla said over lunch at a London hotel.