Last week the Defense Advanced Research Projects Agency announced its latest "grand challenge," which asks teams to develop smart systems that leverage machine learning to optimize available wireless spectrum. With a finite amount of spectrum and a growing number of connected devices, the public and private sector are experiencing a crunch to utilize under-used spectrum and share the available spectrum. "The agency's Spectrum Collaboration Challenge will reward teams for developing smart systems that collaboratively, rather than competitively, adapt in real time to today's fast-changing, congested spectrum environment – redefining the conventional spectrum management roles of humans and machines in order to maximize the flow of radio frequency signals," said DARPA in an announcement Wednesday. The agency unveiled the challenge before some 8000 people at the International Wireless Communications Expo in Las Vegas. The DARPA competition aims to provide an alternative approach to the traditional spectrum allocation process, which pre-assigns exclusive access to designated frequencies.

According to Lee, the program was created as a "chatbot" to entertain 18-to-24 year olds and learn from interacting with humans. However, some Twitter users were able to manipulate the program to send out the offensive messages. "Unfortunately, in the first 24 hours of coming online, a coordinated attack by a subset of people exploited a vulnerability in Tay," Lee explained. Alastair Bathgate, CEO of Blue Prism, a software company that develops robotic process automation systems, said the incident proves that Microsoft has not learnt to control its AI program. "You can be devious with these things because, essentially, they are not that intelligent," he told CNBC over the phone.

Yann LeCun invited me to speak at this week's inaugural symposium on "The Future of AI" at NYU. It's an amazing gathering of leaders in the field to discuss the state of AI and its continued advancement. Here's what I talked about -- how deep learning is a new software model that needs a new computing model; why AI researchers have adopted GPU-accelerated computing; and NVIDIA's ongoing efforts to advance AI as we enter into its exponential adoption. And why, after all these years, AI has taken off. For as long as we have been designing computers, AI has been the final frontier.

Machine learning is the idea that there are generic algorithms that can tell you something interesting about a set of data without you having to write any custom code specific to the problem. Instead of writing code, you feed data to the generic algorithm and it builds its own logic based on the data. For example, one kind of algorithm is a classification algorithm. It can put data into different groups. The same classification algorithm used to recognize handwritten numbers could also be used to classify emails into spam and not-spam without changing a line of code.

Deep Learning is a new area of Machine Learning research that has been gaining significant media interest owing to the role it is playing in artificial intelligence applications like image recognition, self-driving cars and most recently the AlphaGo vs. Lee Sedol matches. Recently, Deep Learning techniques have become popular in solving traditional Natural Language Processing problems like Sentiment Analysis. For those of you that are new to the topic of Deep Learning, we have put together a list of ten common terms and concepts explained in simple English, which will hopefully make them a bit easier to understand. We've done the same in the past for Machine Learning and NLP terms, which you might also find interesting. In the human brain, a neuron is a cell that processes and transmits information.

Industry experts estimate that data volumes are doubling in size every two years. Managing all of this is a challenge for any enterprise, but it's not just the volume of data as much as the variety of data that presents a problems. With SaaS and on-premises applications, machine data, and mobile apps all proliferating, we are seeing the rise of an increasingly complicated value-chain ecosystem. IT leaders need to incorporate a portfolio-based approach and combine cloud and on-premises deployment models to sustain competitive advantage. Improving the scale and flexibility of data integration across both environments to deliver a hybrid offering is necessary to provide the right data to the right people at the right time.

One of the major announcements to come out of Microsoft's Build 2016 developer conference today was the bet the company is making on bots. Microsoft believes that bots are the new apps. Yesterday, they invited developers to build bots for Cortana, the company's virtual assistant. Cortana, for you non-gamers, is a virtual persona character from Microsoft's blockbuster first-person shooter Halo franchise. Microsoft is betting on the notion of "conversational computing," which is why the company is putting its voice recognizing virtual assistant front and center.

Artificial Intelligence is transforming the job board space. Increasingly, AI is being used to process online applications and categorize applicants into priority rankings. One example of how the process of applying for jobs is changing can be seen in innovations recently put into place on the icrunchdata job posting platform. The company uses AI to connect employers and job seekers in the high-demand data science niche. It launched its new job posting platform last month.

Humans have a long and storied history of freaking out over the possible effects of our technologies. Long ago, Plato worried that writing would hurt people's memories and "implant forgetfulness in their souls." More recently, Mary Shelley's tale of Frankenstein's monster warned us against playing God. Today, as artificial intelligences multiply, our ethical dilemmas have grown thornier. That's because AI can (and often should) behave in ways human creators might not expect.

The incident marks another embarrassing setback for the software company as it tries to get ahead of Alphabet Inc's Google, Facebook Inc and other tech firms in the race to create virtual agents that can interact with people and learn from them. The TayTweets (@TayandYou) Twitter handle was made private and the chatbot stopped responding to comments Wednesday morning after it fired off the same tweet to many users. "You are too fast, please take a rest...," tweeted Tay to hundreds of Twitter profiles, according to screen images published by technology news website The Verge. Tay's Twitter account was accidentally turned back on while the company was fixing the problems that came to light last week, Microsoft said on Wednesday. "Tay remains offline while we make adjustments," a Microsoft representative said in an email.