Shares of Intel (NASDAQ:INTC) have been trading along the 100-day moving average after bouncing off the low in February, as analysts raised concerns about PC and notebook sales during the first-quarter 2016. Intel will report its first-quarter 2016 earnings after the market close on April 19. Investors will be closely watching the results from the Client Computing Group, or CCG, Intel's mobile and PC business, and the Data Center Group, or DCG, as about 88.9% of their revenues last year came from these two groups. Less than a week ahead of the earnings report, Pacific Crest warned it expects Intel to report first-quarter earnings below the midpoint of guidance, and to lower its guidance for the full-year as well. Wall Street opinions about Intel's data center outlook are mixed, according to Barron's.

Rapid advancements in artificial intelligence (AI) has led many to ask questions about what if these intelligent machines and robots start acting unethically? This has led many to go to the extreme demanding for an outright ban on robotics and AI research while others are calling for more research to understand how AI might be constrained. But how can robots learn ethical behavior if there is no "user manual" for being human? Researchers Mark Riedl and Brent Harrison from the School of Interactive Computing at the Georgia Institute of Technology believe the answer lies in "Quixote" -- to be unveiled at the AAAI-16 Conference in Phoenix, Ariz. Quixote teaches "value alignment" to robots by training them to read stories, learn acceptable sequences of events and understand successful ways to behave in human societies.

John Williams is well-known for his melodies in his music for films and concerts. In today's episode of Film Cue Review, we find out that his gift to support the film goes much deeper than we had anticipated. We take a look at his harmonic and orchestrational choices on the cue "Hide & Seek" from Steven Spielberg's 2001 film, Artificial Intelligence.

The green tractor trundling across a Manitoba field with an empty cab looks like it's on a collision course with Matt Reimer's combine--until it neatly turns to pull alongside so he can pour freshly harvested wheat into its trailer. It's an eight-year-old John Deere that the 30-year-old Mr. Reimer modified with drone parts, open-source software and a Microsoft Corp. MSFT 1.52 % tablet. All told, those items cost him around 8,000. He said that's about how much he saved on wages for drivers helping with last year's harvest. Mr. Reimer's alterations, which he hopes to replicate for other farmers this year, are part of a technology revolution sweeping North America's breadbasket.

Neither humans nor AI has proven overwhelmingly successful at maintaining cybersecurity on their own, so why not see what happens when you combine the two? That's exactly the premise of a new project from MIT, and it's achieved some pretty impressive results. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and machine-learning startup PatternEx have developed a new platform called AI2 that can detect 85 percent of attacks. It also reduces the number of "false positives" -- nonthreats mistakenly identified as threats -- by a factor of five, the researchers said. The system was tested on 3.6 billion pieces of data generated by millions of users over a period of three months.

A NASA-developed air traffic control system for drones could take a major step forward this week when up to 24 drones take to the skies from locations across the U.S. in the agency's first coordinated test. Called UTM, for unmanned aircraft system traffic management, the platform is seen as a key safety system that would allow greater numbers of drones to fly in the sky and avoid mid-air collisions with piloted aircraft and other drones. It allows drone operators to enter a flight plan and request clearance for the flight. The system checks the plan for conflicts with other planned drone flights and accepts or rejects it. For example, a farmer could program a drone flight above her land, effectively reserving it for a certain period of time, and then carry out the flight in the knowledge that a delivery drone scheduled to arrive at the same time will automatically calculate a path to avoid a collision.

Funding dollars to Internet of Things startups jumped 31% in the first quarter of this year, compared to Q4'15. That was the second-highest total yet in a quarter. As industrial and business processes are more frequently mediated by the IoT, and IoT-driven analytics solidifies as a category, startups are leveraging machine learning and deep learning to provide predictive insights based on the data collected from wearables and sensors. Just in the last quarter, companies like Tellmeplus, Neura, and Sentenai raised funds to integrate machine learning algorithms with different IoT functions, including data collection, sorting, analyzing, insights, and automation. "A good IoT solution gives you an extraordinarily useful view of your organization's data; a great one allows you to build algorithms that can predict what's next…" – Microsoft IoT blog.

In 2011, Ian Burkhart, a college freshman, broke his neck while diving into a wave in North Carolina. His spinal injury left him paralyzed from the chest down, a quadriplegic, his brain no longer able to communicate with his limbs. Last week, neural engineers at Ohio State University, activated a computer chip that had been surgically implanted in Mr. Burkhart's brain, bypassing his spinal cord they rerouted his brain signals directly to his arm, and allowed him to pick up objects, stir liquids and play guitar video games - using his own thoughts. Dr. Ali Rezai, the surgeon and director of Ohio State's Center for Neuromodulation, implanted the eraser-head sized chip, using brain imaging to find the precise location with Mr. Burkhart's motor cortex that controls hand movements. The chip holds 96 "microelectrodes" that record the firing patterns of individual neurons.

When creating a culture of innovation, many organizations face hurdles related to talent, capital and time. CIOs and the enterprises they lead are now at an inflection point in the way that humans and technology work together in the business ecosystem, with companies utilizing cognitive automation as a way to shift workflow dynamics and unleash the potential for every employee to be an innovator. The opportunity for cognitive automation is so great that industry analysts predict that by 2020, smart machines will become a top five investment priority for almost a third of CIOs. By mimicking human activities such as perceiving, inferring, gathering evidence and probabilistic reasoning, cognitive systems can perform tasks that have historically required human intelligence and situational analysis. The co-existence between human employees and cognitive systems is creating a new class of digital labor that can enhance human skills and expertise, allowing employees to innovate constantly. Working within this new ecosystem, generalists can behave like specialists, and less experienced employees can perform like seasoned veterans.

We can predict the future, to an extent. Science-fiction writer Isaac Asimov, often cited by futurist Ray Kurzweil as an influential thought leader in the classic debate between man and machine, theorized that human behavior can be predicted in aggregate over a long period of time. So, if we believe that past behavior is a good predictor of future behavior, we can take a good guess at what the far future holds for us. If this pattern continues, then the next generation of technology will be autonomous. We're already seeing this become a reality.