If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
ReSpeaker has released its 4-Microphone Raspberry Pi HAT (Hardware Attached on Top), a quad-microphone expansion board for Raspberry Pi which has been designed for AI assistant and voice applications. This board will enable you to build your own voice interaction application, or create your own AI assistant. The board can be used in robotics or in smart homes, IoT scenarios, and conference rooms, and is customisable as you add new modules. The board has been developed based on AC108, an integrated quad-channel ADC (Analog to Digital Converter) with I2S/TDM (Time Division Multiplexing) output transition which will give a high definition voice capture. The four microphone version also comes with an LED ring, which will flash in the direction of your voice.
BOSTON – Self-driving cars may not hit the road in earnest for many years -- but autonomous boats could be just around the pier. Spurred in part by the car industry's race to build driverless vehicles, marine innovators are building automated ferry boats for Amsterdam canals, cargo ships that can steer themselves through Norwegian fjords and remote-controlled ships to carry containers across the Atlantic and Pacific. The first such autonomous ships could be in operation within three years. One experimental workboat spent this summer dodging tall ships and tankers in Boston Harbor, outfitted with sensors and self-navigating software and emblazoned with the words "UNMANNED VESSEL" across its aluminum hull. "We're in full autonomy now," said Jeff Gawrys, a marine technician for Boston start-up Sea Machines Robotics, sitting at the helm as the boat floated through a harbor channel.
Episode Info: Welcome to episode #583 of Six Pixels Of Separation - The Mirum Podcast. Here it is: Six Pixels Of Separation - The Mirum Podcast - Episode #583 - Host: Mitch Joel. He considers himself a "professional explainer." I've known Jim Sterne for over a decade. He sold business computers to first-time owners in the 1980s, consulted and keynoted about online marketing in the 1990s, founded a conference and a professional association around digital analytics in the 2000s, and recently published his twelfth book (yes, twelfth!), Artificial Intelligence for Marketing.
Machine learning is a hot topic across the technology spectrum today. From self-driving cars, to catching nefarious content in the fight against terrorism, to apps that automatically retouch photos before you even take them, it is popping up just about everywhere. Each innovation is creating a new wave of business opportunity while simplifying and automating tasks that are generally beyond the reach of how much data we human beings can process at once, or even in a lifetime. While machine learning might seem a newly emerging trend – which it most certainly is – it is also a breakthrough that has been a long time coming. Back in 1959, computer science and gaming pioneer Arthur Samuel defined machine learning as giving "computers the ability to learn without being explicitly programmed."
And among the things we urgently need to learn more about is not just how artificial intelligence works, but how humans work. Humans are also the only species to have developed "group normativity" – an elaborate system of rules and norms that designate what is collectively acceptable and not acceptable for other people to do, kept in check by group efforts to punish those who break the rules. But our complex normative social orders are less about ethical choices than they are about the coordination of billions of people making millions of choices on a daily basis about how to behave. Are we prepared for AIs that start building their own normative systems--their own rules about what is acceptable and unacceptable for a machine to do--in order to coordinate their own interactions?
As with many other services, the legal profession is undergoing digital transformation. Established firms are facing competition from aggressive startups running digital only platforms. This disruption is requiring legacy firms to adapt. Meeting the challenge of digital transformation is not only necessary to remain competitive in terms of offering alternative channels, the use of digital technology can also assist with the amount of work involved with the legal process. As firms seek to adapt, machine learning is being adopted more and more in order to help companies grow more efficient and produce greater value from their processes.
More than a decade back while joining a large US Credit Cards company, it was surprising to see that Predictive Analytics was limited to multivariate regression and logistic models. This was in contrast to previous stints at Start-Ups funded by NASA / NIST where a broader set of Machine Learning (ML) methods including SVMs, NNs, Random or Gradient Boosting Trees were regularly applied. There were a number of good reasons for using the simpler models in Retail Lending. Firstly, Decision Frameworks were already in place that made input feature selection a relatively simpler exercise. For e.g., for Credit Decisioning, one could think in terms of 5Cs of Credit (Character, Capacity, Capital, Collateral, Conditions), and search for Data variables that catered to them.
Ever wish you could weed out misogynist jerks from your dating pool? Starting today, it might get a little easier. OkCupid is partnering with Planned Parenthood to help identify feminist users. By answering one question, you'll be able to find people who share the same view as you and they'll be able to show themselves for the thoughtful people they hopefully (hopefully) are. SEE ALSO: OkCupid launches anti-dick pic pledge to cut down on harassment.
As robots get more advanced and perform more complicated tasks, such as conducting a philharmonic orchestra in Italy, there is still one thing the machines certainly cannot do: feel. However, if scientists from the University of Houston have anything to say about it, that may change soon, at least insofar as the sense of touch is concerned. Cunjiang Yu, an assistant professor at the university and three other researchers created "a semiconductor in a rubber composite format" that can stretch and still retain functionality, allowing a robotic hand to feel temperature differences and distinguish between hot and cold. Writing in the journal Science Advances, they described "a new mechanism for producing stretchable electronics, a process that relies upon readily available materials and could be scaled up for commercial production," according to a statement on the university' website. Semiconductors are usually brittle and incorporating them into stretchable materials usually involves complicated procedures, Yu said in the statement, making the resulting materials both less stable and more expensive than the new material created by his team.
A tech startup called Bodega that hopes to replace mom-and-pop shops with unmanned boxes that rely on an app and artificial intelligence is facing a massive backlash from immigrant business owners and skeptics across Silicon Valley. The company, founded by two former Google employees and launched on Wednesday, is marketing five-foot-wide pantries that users can unlock with their smartphones to pick up non-perishable items. There are no humans at the "stores" – which are already stationed in spots like apartment buildings, offices and gyms – and a computer program automatically charges customers' credit cards, according to Fast Company, which first reported on the startup. Although the boxes appear to be little more than glorified vending machines, the company's executives have been widely mocked, and criticized for explicitly stating that their mission is to displace neighborhood corner stores and put family-owned shops out of business. "The vision here is much bigger than the box itself," co-founder Paul McDonald, a former Google product manager, told Fast Company.