MIT scientists investigate memorization risk in the age of clinical AI
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
cybersecurity
6 Cybersecurity Predictions for the AI Economy in 2026 – SPONSOR CONTENT FROM PALO ALTO NETWORKS
Sponsor Content from Palo Alto Networks.
Read MoreNew MIT program to train military leaders for the AI age
The new certificate program will equip naval officers with skills needed to solve the military’s hardest problems.
Read MoreHow a Transparent Company Culture Strengthens Cybersecurity and Data Resilience – SPONSOR CONTENT FROM VEEAM
Sponsor content from Veeam.
Read MoreHow AI Will Forge the Next Generation of Cybersecurity Talent – SPONSOR CONTENT FROM PALO ALTO NETWORKS
Sponsor Content from Palo Alto Networks.
Read MoreLincoln Lab unveils the most powerful AI supercomputer at any US university
Optimized for generative AI, TX-GAIN is driving innovation in biodefense, materials discovery, cybersecurity, and other areas of research and development.
Read MoreCreate a Company Culture That Takes Cybersecurity Seriously
How to inspire action using behavioral nudges, public commitments, and incentives.
Read MoreBoards Need a More Active Approach to Cybersecurity
Many boards overestimate their company’s cyber-resilience—and underestimate their own role in shaping it.
Read MoreThe approach maintains an AI model’s accuracy while ensuring attackers can’t extract secret information.
Read More3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities
MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.
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