CIO
OCTOBER 24, 2023
In light of this, developer teams are beginning to turn to AI-enabled tools like large language models (LLMs) to simplify and automate tasks. Many developers are beginning to leverage LLMs to accelerate the application coding process, so they can meet deadlines more efficiently without the need for additional resources.
CIO
MARCH 5, 2024
India’s Ministry of Electronics and Information Technology (MeitY) has caused consternation with its stern reminder to makers and users of large language models (LLMs) of their obligations under the country’s IT Act, after Google’s Gemini model was prompted to make derogatory remarks about Indian Prime Minister Narendra Modi.
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AWS Machine Learning - AI
FEBRUARY 6, 2024
To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.
Prisma Clud
JULY 20, 2023
LLM and Cloud Security Let’s explore the relationship between LLMs and cloud security, discussing how these advanced models can be dangerous, as well as leveraged to improve the overall security posture of cloud-based systems. Examples of LLMs include OpenAI's ChatGPT, Google’s Bard and Microsoft's new Bing search engine.
CIO
APRIL 25, 2024
For the business- and employment-focused social media platform, connecting qualified candidates with potential employers to help fill job openings is core business. So the social media giant launched a generative AI journey and is now reporting the results of its experience leveraging Microsoft’s Azure OpenAI Service.
AWS Machine Learning - AI
MARCH 28, 2024
Large language models (LLMs) are generally trained on large publicly available datasets that are domain agnostic. For example, Meta’s Llama models are trained on datasets such as CommonCrawl , C4 , Wikipedia, and ArXiv. These datasets encompass a broad range of topics and domains.
CIO
SEPTEMBER 8, 2023
At work, we’re efficient at processing multiple inputs in rapid time to take into account issues of safety, social norms, the needs of our colleagues and employer, as well as accuracy and strategic goals. Hallucinations can be reduced within enterprise deployments by fine-tuning LLMs through training them on private data that’s been verified.
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