Forbes "30 under 30″ list celebrates the achievements of 30 game changers in 20 different industries -- 600 in total -- of the brightest young entrepreneurs and innovators who are challenging conventional wisdom. The list highlights some interesting trends in robotics, AI, intelligence energy storage, and automation. Connected/smart consumer goods, advanced manufacturing, and artificial intelligence are big ticket items for 2017. Forbes also unveiled its second annual "30 Under 30 Europe" list, featuring 300 young innovators, covering 10 categories. The entire list can be viewed here.

Google is on its way to bringing artificial intelligence and machine learning tools to computer Raspberry Pi. The cheap tiny computer is often used in schools and the maker community for programming devices. Google has set up its very own survey and is asking makers what smart tools would be the "most helpful". In the past Google, has developed a wide range of tools for machine learning such as internet of things devices, wearables, robotics and home automation. Eben Upton, founder of the Raspberry Pi Foundation, told the BBC: "It's fantastic to see Google getting closer to the maker community."

Most of these concepts should hold deep meaning for you: Hyperparameter optimization, Hilbert space, BFGS, Spectral clustering, EM, Multinomial logistic regression Superb communication skills. This is often added to job requirements as an afterthought. You'll need to explain yourself and your methods. Excellent data analysis & visualization skills using tools like R or Python Orbital Insight is a fast growing provider of geospatial data and geo -analytic services to commercial, nonprofit and public sector clients across the globe. Leveraging advancements in computer vision and cloud computing, Orbital Insight is turning millions of images into a big picture understanding of the world that is quantitatively grounded in observation, creating unprecedented transparency, and empowering global decision makers with new sources of objective, quantified socio -economic insights.

Autonomous cars, personal assistants, and robots that give yoga lessons. For better or worse, the world of AI has arrived. In the beginning of January, businesses and journalists of all sorts converged on Las Vegas for the annual CES conference for consumer electronics and consumer technologies. While many of the products showcased and announced during the four-day hullabaloo aren't of particular interest to us--8k TVs and virtual reality headsets, for example--we were intrigued by the significant presence of artificial intelligence products this year. It permeated just about every type of product, and, for many businesses, is at their forefront of their efforts moving into 2017 and beyond.

Learning to reinforcement learn by Jane X Wang, Zeb Kurth-Nelson, Dhruva Tirumala, Hubert Soyer, Joel Z Leibo, Remi Munos, Charles Blundell, Dharshan Kumaran, Matt Botvinick In recent years deep reinforcement learning (RL) systems have attained superhuman performance in a number of challenging task domains. However, a major limitation of such applications is their demand for massive amounts of training data. A critical present objective is thus to develop deep RL methods that can adapt rapidly to new tasks. In the present work we introduce a novel approach to this challenge, which we refer to as deep meta-reinforcement learning. Previous work has shown that recurrent networks can support meta-learning in a fully supervised context.

The only thing that flies faster than time is the progress of technology. Once after lunch, a chip-designing friend excused himself quickly with the deft explanation that Moore's Law meant that he had to make his chip set 0.67 percent faster each week, even while on vacation. Now that 2017 is here, it's time to take stock of the technological changes ahead, if only to help you know where to place your bets in building programming skills for the future. From the increasing security headache of the internet of things to machine learning everywhere, the future of programming keeps getting harder to predict. There are naysayers who claim the chip companies have hit a wall.

It started as a seemingly sweet Twitter chatbot. Modeled after a millennial, it awakened on the internet from behind a pixelated image of a full-lipped young female with a wide and staring gaze. Microsoft, the multinational technology company that created the bot, named it Tay, assigned it a gender, and gave "her" account a tagline that promised, "The more you talk the smarter Tay gets!" She brimmed with enthusiasm: "can i just say that im stoked to meet u? humans are super cool." She asked innocent questions: "Why isn't #NationalPuppyDay everyday?" Tay's designers built her to be a creature of the web, reliant on artificial intelligence (AI) to learn and engage in human conversations and get better at it by interacting with people over social media. As the day went on, Tay gained followers. She also quickly fell prey to Twitter users targeting her vulnerabilities. For those internet antagonists looking to manipulate Tay, it didn't take much effort; they engaged the bot in ugly conversations, tricking the technology into mimicking their racist and sexist behavior.

There is no denying that we are entering a new phase in how technology helps to connect brands with consumers. We are moving from visual interfaces to text and voice. Speaking to our devices like we speak to our friends, family and colleagues. As messenger apps secure the lion's share of our connected time, customers will increasingly expect and want to interact with brands in these channels. And Facebook, and Viber, and Kik, want to connect you with brands on their platform, like (most of) China does on WeChat which has 800 million users and millions of services available within the app.

TLDR; Virtual Reality can be immersive and fun, but add natural deep Artificial Intelligence and you quite literally get a new world which -- beyond the computer generated world around you -- may not actually be so virtual. As applications in Virtual Reality are increasing in quality and variety, early developers are providing us with new interaction dynamics that are expanding the richness of immersive virtual worlds. By layering in aspects of natural artificial intelligence, experiences are developing that lose the feeling of being so "unreal;" distinct memories, interactions and relationships are being created that cause the user to question -- well, if it happens in real life, but inside of a headset, does that not make it real? Of our five senses, Head Mounted Displays (HMDs) handle vision, a solid pair of 3D headphones like OSSIC handle sound; AxonVR and others are working on haptics and touch…next up is smell and taste, those should be, well…interesting. But beyond our five senses which create the feeling of physical "presence" in a virtual space, is the "immersion" of having a real experience, experiencing the unexpected and having the opportunity to create very real memories.

Sears wants to use artificial intelligence to help to shop for your next tire. Sears Auto Center announced the pilot launch of its Digital Tire Journey, a web app that uses IBM Watson Natural Language Classifier service to help customers find the best tires that fit their needs. Hoffman Estates-based Sears says that beyond a vehicle's make and model, customers need tires that are built for their everyday routines, and its new AI-powered site is designed to make the shopping experience more efficient. Rather than using a drop down menu with available selections, Sears' Digital Tire Journey provides tire recommendations based on a customers answer to certain questions. The program asks questions like: "When it comes to tires, what's most important to you?"