Muhammad Tanvir’s Post

While influencers and tech leaders discuss the impact of AI on society and our digital infrastructure, developers are busy training data sets, refining models, and integrating AI into their products and services. For those of us tasked with defending enterprises, the rise of AI introduces new challenges with additional services and systems to secure. In the race to develop AI, it's easy to overlook the security of the underlying systems where AI innovation happens. Read on to learn about securing #AWS Bedrock, a popular service for creating and managing AI workflows and models. https://lnkd.in/ek2GSr9B #AI #ArtificialIntelligence #AIModels #AWSBedrock #Cybersecurity

New tools in Azure AI to help you build more secure and trustworthy generative AI applications ➡ https://lnkd.in/ee4E_VG6 #Azure #AI #AzureAI #MicrosoftAzure

Understanding Red Teaming for Generative AI Red teaming, from military roots, tests IT and AI models for vulnerabilities, aiding cybersecurity. Human involvement is key for interactive AI testing. https://lnkd.in/dzWq2H-i #cloud #cioexcellence #CloudComputing #cloudcentricapplications #datacenter #digitaltransformations #CloudComputing #cloudcentricapplications #genai

In a world of generative AI, getting control over hallucinations is important. Now, Azure AI customers can benefit from Groundedness Detection, a first-of-its-kind feature available on a cloud platform that identifies and block “hallucinations” in outputs to increase their accuracy and usefulness. But there is more, read below to find out about other tools available that you can use to help ensure more secure and trustworthy generative AI applications such as: Prompt Shields, Safety system messages, safety evaluations and Risk and safety monitoring.

Announcing new tools in Azure AI to help you build more secure and trustworthy generative AI applications Azure AI is introducing new tools to address the security and reliability concerns in generative AI. Tools like Prompt Shields, Groundedness detection, Safety system messages, Safety evaluations, and Risk and safety monitoring are being introduced or are available in preview in Azure AI Studio. These tools aim to safeguard applications and improve the quality of generative AI outputs.

Exciting news for AI enthusiasts! Azure AI has just announced new tools that will help build more secure and trustworthy generative AI applications. With these new features, you can ensure that your models behave safely and securely. Check out the link below to learn more about these awesome new features in Azure AI! #Microsoft #AI #Azure #AzureAI https://t.co/5vsgGiXGOL

We’ve made tools available at Azure AI, aimed at helping engineers to build secure & trustworthy generative AI applications. Microsoft Azure

How Safe is Google Cloud for Running Generative AI Applications #AI #ML #MachineLearning #ArtificialIntelligence #ViratKothari #ChatGPT #Technology #TechNews #Research #Tech #DrViratkumarKothari #GenerativeAI

Great article to read on building secure and trustworthy AI. Links to deep dive articles and learning. These tools are a welcome addition.

**New AI Assisted Safety Evaluations** A lot of this post covers existing or renamed features, but the new AI Assisted Safety Evaluations feature is new, and looks great. Some of this is similar to the PromptBench project that was released back in December, but which was in a very early state at the time. This new feature also adds some nice tooling to compare safety scores for two prompts side-by-side, as jailbreak tests evolve. These capabilities are going to become huge for building trust, since most black box protection features remain poorly adopted in an enforced mode. You need to be able to inspect behaviours before you can turn them over to Microsoft to let them control what can, and cannot be done. In any case, this is really good to see. Keen to get to work with it. https://lnkd.in/eQN5cw3H