I recently started a new newsletter focus on AI education and already has over 50,000 subscribers. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Last year, Facebook AI Research(FAIR) open sourced BlenderBot 1.0, the largest open domain chatbot ever built. BlenderBot is able to engage in a large variety of conversations across nearly any topic while displaying human-like characteristics such as empathy and personable levels of engagement.

As is so often the case, the giants of the Internet are chasing the same sparkly vision of the future: chatbots. In the coming months and years, these companies promise, you'll chat with Internet services in much the same way you now chat with friends and family. Bots will instantly answer questions, respond to requests, and even anticipate your needs. While chatting with some some old college pals about an upcoming reunion, you'll ask an OpenTable bot for restaurant recommendations. Google's New Allo Messaging App Gets Its Edge From AI Google Has Open Sourced SyntaxNet, Its AI for Understanding Language Facebook Open Sources Its AI Hardware as It Races Google Google's New Allo Messaging App Gets Its Edge From AI Google's New Allo Messaging App Gets Its Edge From AI But a major challenge remains: building chatbots that can actually chat.

Facebook's AI hardware is now, like its software, open source, joining a broad movement towards outsourcing the world's artificial intelligence intelligence. Facebook also stated it hoped independent AI technicians would develop deep learning tech superior to what the company currently uses, and that it would buy this technology. The tech giant has developed deep learning technology, which it uses for Facebook-related functions like identifying faces in pictures and curating news feeds, but can also apply to a wide range of computing tasks. Through the Open Compute Project, Facebook's custom hardware designs -- a GPU-based server called "Big Sur" -- will join Google's and others' open source deep learning designs. The hope is that more workers will devote themselves to these projects and become familiar with using the technology.