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) …
Everyone's trying to get ready for roads that will be filled with more and more self-driving cars. But just as the first cars were imagined to be like horse-drawn carriages without the horses, it's easy to fall into the trap of thinking that a future with self-driving cars won't be that different -- except that we won't have to drive. As a scientist who specializes in imagination and human behavior, it's interesting to me to try to figure out how technology will change our world. It can be challenging to predict how things will change. But one thing that is important to think about is that self-driving vehicles will be able to go places without anybody in them.
Explainable AI cannot be implemented as an afterthought or add-on to an existing system. It must be part of the original design. Beyond Limits systems cover the full spectrum of explainability, providing high-level system alerts, plus drill-down reasoning traces with detailed evidence, probability, and risk. Explainable AI helps take the mystery out of the technology and is the first step in enabling artificial intelligence to work with people in a trusting and mutually beneficial relationship.
A few days back, Joe McKendrick wrote about an IBM study showing seven business areas that are ripe for AI. It's just part of the onrush of developments that are making AI mainstream. And so it's easy to get jaded when you hear an announcement of yet another AI-enhanced tool. So when we saw an announcement from the tiny startup Obviously AI, we were expecting to see yet another refinement in what we term guided analytics. That's analytics where machine learning is employed to help you choose the best data sets, ask the right questions, and frame the narrative with the best visualizations.
AIQ, the brain behind Signal AI's media monitoring and market intelligence platform, will upgrade the organisation's proprietary artificial intelligence Signal AI, one of the leading companies transforming how business leaders make sense of the world's information, has announced the launch of AIQ, the next generation of AI technology powering their media monitoring and market intelligence platform. AIQ enhances the proprietary artificial intelligence underpinning Signal AI's platform and heralds a step-change in the use of AI to address common public relations challenges. The PR and communications industry is poorly served by incumbent legacy technology that has failed to meaningfully integrate artificial intelligence. Signal AI's introduction of AIQ to the market further distinguishes them as the pioneer in this space, offering real AI technology that delivers tangible results to PR professionals and beyond. The first in a series of new features to be powered by AIQ will be Signal AI's "Briefings".
One cannot introduce AutoML without mentioning the machine learning project's life cycle, which includes data cleaning, feature selection/engineering, model selection, parameter optimization, and finally, model validation. As advanced as technology has become, the traditional data science project still incorporates a lot of manual processes and remains time-consuming and repetitive. AutoML came into the picture to automate the entire process from data cleaning to parameter optimization. It provides tremendous value for machine learning projects in terms of both time savings and performance. Launched in 2018, Google Cloud AutoML quickly gained popularity with its user-friendly interface and high performance.
The latest survey from the World Economic Forum reveals AI adoption will increase across the financial industry within the next two years. A joint survey released by the World Economic Forum and Cambridge Centre for Alternative Finance (CCAF) reveals that while only 16% of companies in the financial sector are using AI tools today, over the next two years, the number is bound to increase to a huge 64% of all financial services brands. What is even more interesting is that 77% of them say they expect AI will become essential to their business. The survey titled'In Transforming Paradigms: Global AI in Financial Services Survey' is based on more than 150 senior financial services executives in FinTech and incumbent financial institutions. As per the survey, the majority of enterprises – 60%- invest less than 10% of R&D resources in AI despite evidence of accelerating returns.
Gaby Ecanow loves listening to music, but never considered writing her own until taking 6.S191 (Introduction to Deep Learning). By her second class, the second-year MIT student had composed an original Irish folk song with the help of a recurrent neural network, and was considering how to adapt the model to create her own Louis the Child-inspired dance beats. "It was cool," she says. "It didn't sound at all like a machine had made it." This year, 6.S191 kicked off as usual, with students spilling into the aisles of Stata Center's Kirsch Auditorium during Independent Activities Period (IAP).
We're living in an age of mass, democratised creativity – or at least that's what the technology industry likes to tell us. You can shoot a movie or record an album on a smartphone, you can become a household name with a webcam and a YouTube channel, and you can download any of a dozen applications and build a video game from nothing. But the latter is an intimidating notion. Games are ultimately complex mechanisms, constructed from code, involving physics, narrative, animation and audio. There has been a deliberate effort within the industry to make creative tools more accessible, arguably spearheaded by Unity, a technology that both powers games and lets users create them – and yet, designing and constructing a game can feel overwhelming.
The Metropolitan police commissioner, Cressida Dick, has attacked critics of facial recognition technology for using arguments she has claimed are highly inaccurate and ill-informed. The Met began operational use of the technology earlier this month despite concerns raised about its accuracy and privacy implications by civil liberties groups, including Amnesty International UK, Liberty and Big Brother Watch (BBW). On Monday, speaking at the Royal United Services Institute (Rusi) in central London, which has just launched its own report expressing reservations about the rollout of new technology in policing, Dick launched an impassioned defence of its use. "I and others have been making the case for the proportionate use of tech in policing, but right now the loudest voices in the debate seem to be the critics, sometimes highly incorrect and/or highly ill-informed," she said. "And I would say it is for the critics to justify to victims of crimes why police shouldn't use tech lawfully and proportionately to catch criminals."