- Massachusetts Institute of Technology - MIT News
Teaching AI models the broad strokes to sketch more like humans do SketchAgent, a drawing system developed by MIT CSAIL researchers, sketches up concepts stroke-by-stroke, teaching language models to visually express concepts on their own and collaborate with humans
- Explained: Generative AI’s environmental impact - MIT News
Plus, generative AI models have an especially short shelf-life, driven by rising demand for new AI applications Companies release new models every few weeks, so the energy used to train prior versions goes to waste, Bashir adds New models often consume more energy for training, since they usually have more parameters than their predecessors
- MIT researchers introduce generative AI for databases
Researchers from MIT and elsewhere developed an easy-to-use tool that enables someone to perform complicated statistical analyses on tabular data using just a few keystrokes Their method combines probabilistic AI models with the programming language SQL to provide faster and more accurate results than other methods
- Helping nonexperts build advanced generative AI models
Last year, that reasoning led to the acquisition of MosaicML by Databricks, a global data storage, analytics, and AI company that works with some of the largest organizations in the world Since the acquisition, the combined companies have released one of the highest performing open-source, general-purpose LLMs yet built
- Explained: Generative AI | MIT News | Massachusetts Institute of Technology
Before the generative AI boom of the past few years, when people talked about AI, typically they were talking about machine-learning models that can learn to make a prediction based on data For instance, such models are trained, using millions of examples, to predict whether a certain X-ray shows signs of a tumor or if a particular borrower is
- Introducing the MIT Generative AI Impact Consortium
The MIT Generative AI Impact Consortium is a collaboration between MIT, founding member companies, and researchers across disciplines who aim to develop open-source generative AI solutions, accelerating innovations in education, research, and industry
- Algorithms and AI for a better world - MIT News
A good example of Raghavan’s intention can be found in his exploration of the use AI in hiring Raghavan says, “It’s hard to argue that hiring practices historically have been particularly good or worth preserving, and tools that learn from historical data inherit all of the biases and mistakes that humans have made in the past ”
- A technique for more effective multipurpose robots
In an effort to train better multipurpose robots, MIT researchers developed a technique to combine multiple sources of data across domains, modalities, and tasks using a type of generative AI known as diffusion models They train a separate diffusion model to learn a strategy, or policy, for completing one task using one specific dataset
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