Amesite, a leading artificial intelligence software company offering a cloud-based learning platform that delivers 99% learner retention for business and education markets, announced an expansion of platform capabilities . Amesite is now delivering features leveraging GPT-3, the engine for ChatGPT, on its learning platform, to complement its existing AI capabilities. Amesite's V5 Customers now have the option to offer learners an AI-assist in explaining challenging concepts and drafting materials, 24/7. An enhanced toolkit will become available on April 2, 2023, with the rollout of Amesite's V6 platform. AI is expected to contribute $15.7T to the global economy by 2030, with the AI software market expected to grow to $1.09T by 2032.

The value of building data-driven businesses with AI at their core is well known today, and business executives are rushing to implement the technology into their operations and gain a competitive advantage, but it's not as simple as creating a data lake and crafting AI models. A large number of AI companies attempting to implement more AI models or build AI-first businesses have experienced challenges. A December 2018 PwC survey found that only 4% of businesses have successfully implemented AI. That's why today the World Economic Forum released the AI toolkit for Boards of Directors. The AI toolkit for Boards of Directors is being released ahead of the annual WEF meeting in Davos, Switzerland where the toolkit will be formally debuted next week.

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Concerns around China's relative weakness in basic AI infrastructure are growing, with some in the industry saying the country needs to create a popular machine learning framework or strengthen existing ones to protect against a doomsday scenario.

"We lived and breathed data science," DataRobot CEO Jeremy Achin says of himself and his cofounder ... [ ] Tom de Godoy. "And we asked ourselves, 'How would we automate our jobs?'" DataRobot wants to make machine learning so simple that a business analyst with basic training can run predictive models without breaking a sweat. The Boston-based startup just raised a $206 million Series E funding round led by Sapphire Ventures to expand the business, which sells software that helps companies across industries develop and deploy in-house AI models. The billion-dollar valuation makes it the highest-ranking of the "picks-and-shovels" startups featured on Forbes' inaugural AI 50 list (meaning the companies that provide tools to help their customers develop their own AI).

"We lived and breathed data science," DataRobot CEO Jeremy Achin says of himself and his cofounder Tom de Godoy. "And we asked ourselves, 'How would we automate our jobs?'" DataRobot wants to make machine learning so simple that a business analyst with basic training can run predictive models without breaking a sweat. The Boston-based startup just raised a $206 million Series E funding round led by Sapphire Ventures to expand the business, which sells software that helps companies across industries develop and deploy in-house AI models. The billion-dollar valuation makes it the highest-ranking of the "picks-and-shovels" startups featured on Forbes' inaugural AI 50 list (meaning the companies that provide tools to help their customers develop their own AI).

"We lived and breathed data science," DataRobot CEO Jeremy Achin says of himself and his cofounder Tom de Godoy. "And we asked ourselves, 'How would we automate our jobs?'" DataRobot wants to make machine learning so simple that a business analyst with basic training can run their own predictive models without breaking a sweat. The Boston-based startup just raised a $206 million Series E funding round led by Sapphire Ventures to expand the business, which sells software that helps companies across industries develop and deploy their own in-house AI models. The billion-dollar valuation makes it the highest ranking of the "picks-and-shovels" startups featured on Forbes' inaugural AI 50 list (meaning the companies that provides tools to help their customers develop their own AI).

We have prepared this AI toolkit in collaboration with our colleagues at Linklaters. It is based on our shared experience of advising clients on these issues and deploying AI tools in our own business. It draws upon the expertise of lawyers from our technology, privacy, intellectual property, competition, employment and financial services regulatory groups. The toolkit uses Australian law as its reference point but draws on experiences from the EU and the insights apply equally in other jurisdictions. However, it does not consider autonomous vehicles or robotics, which raise their own regulatory and commercial issues. The toolkit starts with a short technical primer.

Azure Machine Learning Service is Microsoft's latest offering for developers and data scientists in the custom cloud machine learning and deep learning category. Azure Machine Learning Service adds to a suite of Azure AI products that includes numerous AI toolkits, chatbot and IoT edge services, data science VMs, and pre-built services for vision, speech, language, knowledge, and search. The AI toolkits include Visual Studio Code Tools for AI, the older drag-and-drop Azure Machine Learning Studio, MMLSpark deep learning tools for Apache Spark, and the Microsoft Cognitive Toolkit, previously known as CNTK, which is being de-emphasized in favor of other machine learning and deep learning frameworks. Using cloud resources for training deep learning models makes eminent sense in many cases. Using the cloud for training doesn't necessarily replace the convenience and low operating cost of using your own computer for model building, especially if you have one with lots of RAM and a capable GPU such as an Nvidia Titan RTX.

AI is a term that gets bandied about a lot these days. But what does it really mean? Luis Perez-Breva is a lecturer and research scientist at MIT's School of Engineering and the originator and lead Instructor of the MIT Innovation Teams Program. He's the author of Innovating: A Doer's Manifesto for Starting from a Hunch, Prototyping Problems, Scaling Up, and Learning to Be Productively Wrong. He knows a lot about what AI is and how it will impact our lives going forward. He also knows a lot about what AI isn't. I recently got a chance to pick his brain, and hopefully clear a few things up.