With businesses uncovering more and more use cases for artificial intelligence and machine learning, data scientists find themselves looking closely at their workflow. There are a myriad of moving pieces in AI and ML development, and they all must be managed with an eye on efficiency and flexible, strong functionality. The challenge now is to … continue reading
A few weeks ago, the National Institute of Standards and Technology (NIST) released Dioptra, an open source tool for testing the trustworthiness of AI models. Dioptra offers a common platform for assessing models throughout their life cycle, from when they are being developed to when they are acquired by other parties who want to then … continue reading
Every year, Forrester puts together a list of 10 emerging technologies to watch. This year’s list was released in June, and in the most recent episode of our podcast, What the Dev?, we were able to sit down with Brian Hopkins, VP of Emerging Tech Portfolio at Forrester, about the list. Here is an edited … continue reading
Good teamwork is key to any successful AI project but combining data scientists and software engineers into an effective force is no easy task. According to Gartner, 30 percent of AI projects will be abandoned by the end of 2025 thanks to factors such as poor data quality, escalating costs and a lack of business … continue reading
Qualys has announced a new tool called Qualys TotalAI that will enable teams to better address the security risks of generative AI. Specifically, it addresses the issues listed in the OWASP Top 10 for LLMs, which includes things like prompt injection, sensitive information disclosure, and model theft. According to Qualys, one of the big challenges … continue reading
GitHub is announcing a new sandbox environment — GitHub Models — where developers can experiment with AI models from different providers right from within GitHub. Developers can access models and then test different prompts and model parameters in a playground environment. “For most of us, learning to be a developer didn’t happen on a linear … continue reading
Developers, it appears, will not be replaced by artificial intelligence – at least not yet, anyway. What they will need to do is learn or improve their skills in providing templates for AI, become masters of fixing problems in AI-generated code, and actually learn the best uses for AI in software development. In its current … continue reading
Earlier this week, Microsoft introduced the Agent Framework to its open source project Semantic Kernel, an SDK that integrates LLMs with C#, Python, and Java so that developers can incorporate AI features into their apps. With this new experimental framework, agents are now supported in the platform. According to Microsoft, agents are AI entities that … continue reading
The White House is issuing recommendations not to restrict the use of open source AI models, based on a report from the Department of Commerce’s National Telecommunications and Information Administration (NTIA). The report recommends open models continue to be monitored for potential risks. Part of NTIA’s recommendation is that the government should start an ongoing … continue reading
OpenAI has announced that it is starting to roll out its advanced Voice Mode to a select group of ChatGPT Plus users. According to the company, this new mode “offers more natural, real-time conversations, allows you to interrupt anytime, and senses and responds to your emotions.” Advanced Voice Mode was tested by over 100 external … continue reading
Pluralsight is on a mission to accelerate learning experiences on its upskilling platform with the launch of a new AI assistant called Iris. Iris helps users more quickly discover content that is relevant to their questions, learning objectives, and goals. It can also make recommendations on the platform’s thousands of learning paths and courses to … continue reading
The AI company Galileo has just announced its latest Hallucination Index, which is a framework that evaluates 22 leading generative AI models. Models are tested using a metric called context adherence, which measures “closed-domain hallucinations: cases where your model said things that were not provided in the context.” The best performing model overall for RAG, … continue reading
