Garry Kasparav, the chess legend defeated Deep Blue', the powerful computer built by IBM in a historic match in 1996. A year later, in a re-match, much to the surprise of many, a vastly improved computer beat the International Grandmaster. What happened was Deep Blue-2' had used the same heuristics as Deep Blue-1, but it was empowered with more CPU power. Today, two decades later, we see significant advances in Artificial Intelligence (AI). IBM's Watson built jeopardy, combined by speech recognition, search and speech generation.

The rush to adopt machine learning practices has become ubiquitous in every industry. Enterprise data scientists want their AI models to be deployed into production to propel their organizations forward. Meanwhile, IT is looking for ways to enable their data scientists to build, train, and deploy their models in a way that does not compromise the security of their organizations, while making efficient use of resources like costly GPU clusters. Anaconda, the creator of Conda, has adopted Kubernetes as the standard for building and deploying ML models at speed and scale in Anaconda Enterprise. Elizabeth Winkler has devoted her career to building SaaS products that leverage natural language processing and machine learning to extract meaning out of massive amounts of data.

Nyansa added support for Cisco, Hewlett Packard Enterprise (HPE), Meraki, Juniper, and Alcatel Lucent hardware to its Voyance AIOPs platform in an effort to eliminate what it's calling IT tool glut. The company claims that by using its software, customers can consolidate their network monitoring and telemetry into a single dashboard and eliminate monitoring tools like Cisco Prime, Aruba Airwave, or SolarWinds. "Customers don't want to have to learn, deploy, get trained on, and pay for a bunch of different performance monitoring systems," said David Callisch, VP of marketing at Nyansa. "They want something that's more modern, that provides more intelligence and analytics to allow them to become more proactive." Callisch added that the problem is compounded for enterprises that use networking equipment from multiple vendors, each of which would normally require its own performance monitoring tools.

In the 19th century, doctors might have prescribed mercury for mood swings and arsenic for asthma. It might not have occurred to them to wash their hands before your surgery. They weren't trying to kill you, of course--they just didn't know any better. These early doctors had valuable data scribbled in their notebooks, but each held only one piece in a grand jigsaw puzzle. Without modern tools for sharing and analyzing information--as well as a science for making sense of that data--there wasn't much to stop superstition from influencing what could be seen through a keyhole of observable facts.

In a country where removing children from their parents is perhaps the most severe intervention the state can make in relation to its citizens, it's no wonder that involving computerised decision-making in the process causes disquiet. Over recent years there have been regular stories in the national media raising alarms over resource-starved councils plugging citizens' data into systems – including within children's services – that seek to predict futures, and advise professionals what to do next. Just a few weeks ago, one of the schemes that has attracted most controversy – Hackney council's Early Help Profiling System (EHPS), commissioned from private provider Xantura – was dropped after it did not "realise the expected benefits". The grant-funded pilot project, profiled last year by Community Care, was intended to help social workers identify children most at risk of harm. Hackney did not respond to an interview request for this piece but, according to a council statement, problems with data quality meant further investment could not be justified.

The Apple credit card has come under scrutiny for offering lower credit limits to women (AP ... [ ] Photo/Tony Avelar, File) The Apple-branded credit card is under scrutiny, because women are receiving less credit than their spouses who share their income and credit score. In launching the card, Apple partnered with Goldman Sachs, and Goldman is the issuing bank for the card. Now, Goldman's credit review process is being labeled sexist by Elizabeth Warren and several high-power tech execs. A tech entrepreneur, David Heinemeier Hansson, first raised the issue when he tweeted that the Apple Card's algorithms discriminated against his wife, giving him 20 times the credit limit it had given to her. Apple cofounder Steve Wozniak weighed in asserting that he can borrow ten times as much as his wife on their Apple Cards.

Wikipedia defines Human in the Loop (HITH) as a model that requires human interaction. HITL is associated with modeling and simulation (M&S) in the live, virtual, and constructive taxonomy. HITL models may conform to human factors requirements as in the case of a mockup. In this type of simulation a human is always part of the simulation and consequently influences the outcome in such a way that is difficult if not impossible to reproduce exactly. HITL also readily allows for the identification of problems and requirements that may not be easily identified by other means of simulation.

Within the voice industry, there is speculation that there's recently been a "trough of disillusionment" following the typical trajectory of a new technology. However, this view stems from a misrecognition of the present and future applications of this transformative technology. While companies may be tempted to wait until the technology matures or achieves perceived market saturation, brands that view their voice strategies as a long-term, strategic play will be well-positioned to benefit from the first-mover advantage. It's time to start thinking now about the expression of your brand through voice-based AI conversation. As more companies consider entering this space, we need to carefully examine this industry to reveal what is truly happening, why progress may feel stalled and what is in store -- not only in the voice industry but also in the tech industry and the U.S. economy -- and what that means for your business. Voice represents a fundamental shift in an economy dominated by technology companies.

Two of the largest drugmakers in the country are investing in a startup applying artificial intelligence in pathology. Boston-based PathAI said Monday that it had closed its $75 million Series B financing round with funding from New York-based Bristol-Myers Squibb and the Merck Global Health Innovation Fund, part of Kenilworth, New Jersey-based Merck & Co. PathAI said it would use the money to bolster its clinical development capabilities. PathAI had announced its $60 million Series B financing its April, led by venture capital firms General Atlantic and General Catalyst, with participation from LabCorp, which the company said the latest investment follows and extends. "Merck, BMS and other strategic partners understand that having these best possible insight into the data is incredibly important for driving continued advancements in the rapidly moving field of immuno-oncology, ultimately helping to bring new and better treatments to patients faster," PathAI CEO Andy Beck said in a statement. According to the company's website, its technology is designed to help pathologists make rapid diagnoses for patients.

Conversational user experiences, in the form of chatbots and voice interfaces, are overtaking many of the traditional ways in which we interact with machines. Since the rise of computers, human-machine interfaces typically had some form of Graphical User Interface (GUI) which enabled direct (if limited) interaction with devices and their programs, for instance via software installs, mobile apps, and web-based applications such as Software as a Service (SaaS). No matter how "beautiful" the respective interface, this GUI is now more and more replaced by a Conversational User Interface (CUI). Other still evolving interface styles are less text- and voice-driven, and therefore limit the messaging element to certain basic functions such as taking photos with the blink of an eye (smart glasses or smart cameras such as Blincam can do that today) but will eventually allow for richer interaction gestures (see project Soli). When coupled with an input-output feedback loop, so-called bionic lenses also hold a promising future.