As the technological progress codified as Moore's Law slows down, computer scientists are turning to alternative methods of computing, such as superconducting quantum processors to deliver computing gains in the future. Jeffrey Welser, vice president and lab director at IBM Research at Almaden, spoke about quantum computing at the 49th annual Semicon West chip manufacturing show in San Francisco last week. I caught up with him to get his take on quantum computing for the layperson. IBM also displayed a part of its IBM Q System at the show, giving us an idea of how much refrigeration technology has to be built around a current quantum processor to ensure its calculations are accurate. Binary digits -- ones and zeroes -- are the basic components of information in classical computers. Quantum bits, or qubits, are built on a much smaller scale. And qubits can be in a state of 0, 1, or both at any given time.

IBM earned a record 9,100 U.S. patents in 2018, marking the 26th year in a row the Armonk, New York-based company has been the top recipient. Samsung was second with 5,850 patents while tech giants Apple and Microsoft also appeared in the top ten, according to a list compiled by research service IFI Claims. IBM's latest patent haul, which topped the 9,043 it received last year, includes a growing number of inventions related to artificial intelligence and quantum computing, which many people see as critical technologies of the future. Google, which came in at number seven on last year's list, did not crack the top ten patent recipients for 2018. Meanwhile, Apple rose to ninth from eleventh.

A lot has been accomplished in the last year to improve comprehension, accuracy and scalability of artificial intelligence, but 2019 will see efforts focused on eliminating bias and making decision making more transparent. Jeff Welser, vice president at IBM Research, says the organization has hit several AI milestones in the past year and is predicting three key areas of focus for 2019. Bringing cognitive solutions powered by AI to a platform businesses can easily adopt is a strategic business imperative for the company, he said, while also increasing understanding of AI and addressing issues such as bias and trust. When it comes to advancing AI, Welser said there's been progress in several areas, including comprehension of speech and analyzing images. IBM's Project Debater work has been able to extend current AI speech comprehension capabilities beyond simple question answering tasks, enabling machines to better understand when people are making arguments, he said, and taking it beyond just "search on steroids."

A lot has been accomplished in the last year to improve comprehension, accuracy and scalability of artificial intelligence, but 2019 will see efforts focused on eliminating bias and making decision making more transparent. Jeff Welser, vice president at IBM Research, says the organization has hit several AI milestones in the past year and is predicting three key areas of focus for 2019. Bringing cognitive solutions powered by AI to a platform businesses can easily adopt is a strategic business imperative for the company, he said, while also increasing understanding of AI and addressing issues such as bias and trust. When it comes to advancing AI, Welser said there's been progress in several areas, including comprehension of speech and analyzing images. IBM's Project Debater work has been able to extend current AI speech comprehension capabilities beyond simple question answering tasks, enabling machines to better understand when people are making arguments, he said, and taking it beyond just "search on steroids."

Computational efficiency is the name of the game in artificial intelligence (AI). It's not easy maintaining a balance between training speed, accuracy, and energy consumption, but recent hardware advances have made the goal more attainable than it once was. The first of the Armonk, New York company's breakthroughs is an accelerated digital technique that achieves full accuracy with 8-bit precision. The second is an 8-bit precision technique for an analog chip -- the highest of its kind to date, IBM claims -- that roughly doubles accuracy. Both were detailed today in Montreal at NeurIPS 2018, one of the world's largest AI and machine learning conferences.

At a small event in San Francisco last night, IBM hosted two debate club-style discussions between two humans and an AI called "Project Debater." The goal was for the AI to engage in a series of reasoned arguments according to some pretty standard rules of debate: no awareness of the debate topic ahead of time, no pre-canned responses. Each side gave a four-minute introductory speech, a four-minute rebuttal to the other's arguments, and a two-minute closing statement. Project Debater held its own. It looks like a huge leap beyond that other splashy demonstration we all remember from IBM when Watson mopped the floor with its competition at Jeopardy.

When the 2008 Summer Olympics were about to open in Beijing, China, government authorities grew increasingly concerned about the city's notorious pollution problem. Rather than risk the health of athletes and guests at the games, dozens of nearby factories were ordered closed and driving restrictions reduced traffic by 90 percent, according to state news reports. While the moves were considered radical and impacted the region's economy, the Beijing government felt it had little choice. Today, Beijing is saturated with sensors that can measure CO2 content and other pollutants. Data from the sensors is now combined with information from the city's weather service and run through algorithms developed by IBM's Almaden Laboratory in Silicon Valley that help to predict whether or not the city is going to be impacted by high levels of pollution.

At a small event in San Francisco last night, IBM hosted two debate club-style discussions between two humans and an AI called "Project Debater." The goal was for the AI to engage in a series of reasoned arguments according to some pretty standard rules of debate: no awareness of the debate topic ahead of time, no pre-canned responses. Each side gave a four-minute introductory speech, a four-minute rebuttal to the other's arguments, and a two-minute closing statement. Project Debater held its own. It looks like a huge leap beyond that other splashy demonstration we all remember from IBM, when Watson mopped the floor with its competition at Jeopardy.

In early 2016, the Office of Personnel Management, the human resources agency for federal employees, began researching software that would track the social media accounts of security clearance applicants. The agency was reportedly looking to contract with companies that could do searches with almost no need for human input and had a "robust identity-matching algorithm" to cut down on mixups. The company's chief competitor is a 10-minute walk from FiscalNote's office, just south of Dupont Circle. Quorum was founded in 2014 by Alex Wirth and Jonathan Marks while they were still Harvard undergrads. Now employing up to 46 people, stuffed into a buzzing glass-partitioned office space marked by caramel-colored wide-board wood floors, the office has a map of the D.C. Metro system embedded in tile on the wall of the open kitchen space.

That's what Jeff Welser, lab director of IBM Research-Almaden told me on a recent visit. Given that IBM's Watson technology was initially a system designed to play the TV game show Jeopardy, but is now a general-purpose machine learning system thought to be the fastest-growing part of IBM's business, it's not surprising that the company is hoping another wild seed will bear profitable fruit. But where do these seeds come from? Welser told me that research projects often originate from open mike sessions, held once a year. These are serious events and, at the same time, entertainment along the lines of Shark Tank meets American Idol.