Artificial Inteligence ChatGPT Security 
CIO
MARCH 31, 2025
The 2024 Security Priorities study shows that for 72% of IT and security decision makers, their roles have expanded to accommodate new challenges, with Risk management, Securing AI-enabled technology and emerging technologies being added to their plate.
CIO
MARCH 20, 2025
Global competition is heating up among large language models (LLMs), with the major players vying for dominance in AI reasoning capabilities and cost efficiency. OpenAI is leading the pack with ChatGPT and DeepSeek, both of which pushed the boundaries of artificial intelligence.
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CIO
DECEMBER 20, 2024
As concerns about AI security, risk, and compliance continue to escalate, practical solutions remain elusive. From the discussions, it is clear that today, the critical focus for CISOs, CIOs, CDOs, and CTOs centers on protecting proprietary AI models from attack and protecting proprietary data from being ingested by public AI models.
TechCrunch
MAY 16, 2023
“Hippocratic has created the first safety-focused large language model (LLM) designed specifically for healthcare,” Shah told TechCrunch in an email interview. The dietary advice use case gave me pause, I must say, in light of the poor diet-related suggestions AI like OpenAI’s ChatGPT provides.
Tenable
NOVEMBER 29, 2024
In this special edition, we’ve selected the most-read Cybersecurity Snapshot items about AI security this year. ICYMI the first time around, check out this roundup of data points, tips and trends about secure AI deployment; shadow AI; AI threat detection; AI risks; AI governance; AI cybersecurity uses — and more.
CIO
NOVEMBER 16, 2023
A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. Deploying public LLMs Dig Security is an Israeli cloud data security company, and its engineers use ChatGPT to write code.
Openxcell
JANUARY 20, 2025
LLM or large language models are deep learning models trained on vast amounts of linguistic data so they understand and respond in natural language (human-like texts). These encoders and decoders help the LLM model contextualize the input data and, based on that, generate appropriate responses.
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