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MIT Technology Review Artificial Intelligence - Software
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Designing better products with AI and sustainability | MIT Technology Review
On a mission to reduce the environmental impact of manufacturing components, Siemens turned its attention to the design of a robot gripper. Making up just 2% of the robot, the impact of this hand-like device may seem inconsequential. But, reducing its weight by 90% and the number of constituent parts by 84% can save up to 3…
The road to artificial general intelligence | MIT Technology Review
Artificial intelligence models that can discover drugs and write code still fail at puzzles a lay person can master in minutes. This phenomenon sits at the heart of the challenge of artificial general intelligence (AGI). Can today’s AI revolution produce models that rival or surpass human intelligence across all domains? If so, what underlying enablers—whether…
The real impact of AI on your organization | MIT Technology Review
AI technologies are reshaping work, but not all workflows or roles will be equally transformed. Discover how AI is changing the way we work, given the technical capabilities and limitations of today’s systems. Through real-world use cases and strategic insights, this session equips business leaders with the knowledge to prioritize investments and identify the technologies…
AI strategies from the front lines | MIT Technology Review
AI’s potential to transform business is undeniable, but realizing tangible value remains a challenge. This session explores where AI is driving the greatest returns today, how to set and manage realistic expectations, and approaches to overcome cultural and operational inertia. Attendees will gain practical guidance and actionable insights to inform their AI strategies and guide…
The future of AI processing | MIT Technology Review
Artificial Intelligence (AI) is emerging in everyday use cases, thanks to advances in foundational models, more powerful chip technology, and abundant data. To become truly embedded and seamless, AI computation must now be distributed—and much of it will take place on device and at the edge. To support this evolution, computation for running AI workloads…
Reframing digital transformation through the lens of generative AI | MIT Technology Review
Enterprise adoption of generative AI technologies has undergone explosive growth in the last two years and counting. Powerful solutions underpinned by this new generation of large language models (LLMs) have been used to accelerate research, automate content creation, and replace clunky chatbots with AI assistants and more sophisticated AI agents that closely mimic human interaction.…
Harnessing cloud and AI to power a sustainable future | MIT Technology Review
Organizations working toward ambitious sustainability targets are finding an ally in emerging technologies. In agriculture, for instance, AI can use satellite imagery and real-time weather data to optimize irrigation and reduce water usage. In urban areas, cloud-enabled AI can power intelligent traffic systems, rerouting vehicles to cut commute times and emissions. At an industrial level, advanced…