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) …
If we sum up all the available numbers for AI research investments (including other government funding like the $93.5M awarded to IVADO by the Canada Research Excellence Fund last September, as well as private funds invested in public or semi-public labs) we end up with close to $500M in funding across the country. Beyond that, when we look up other domains that work hand in hand with AI, such as Big Data, cloud infrastructure and the like, that number grows even higher. What made Silicon Valley's talent pump work up to now was its ecosystem of large firms and venture capital feeding startups, as well as research who in turn generate the innovations to push the large firms forward. With investments from the federal and provincial governments in research, as well as from Big Tech, the Canadian talent pump is growing quickly.
Nvidia has benefitted from a rapid explosion of investment in machine learning from tech companies. Can this rapid growth in the use cases for machine learning continue? Recent research results from applying machine learning to diagnosis are impressive (see "An AI Ophthalmologist Shows How Machine Learning May Transform Medicine"). Your chips are already driving some cars: all Tesla vehicles now use Nvidia's Drive PX 2 computer to power the Autopilot feature that automates highway driving.
There is no doubt that 2016 was a breakthrough year for some of the technologies we have been watching. AI, VR, AR, Chatbots, self-driving cars all took significant leaps forward in terms of their practical applications and adoption, taking many by surprise. It is definitely true to say that the robots are no longer coming- they are here, and they are taking jobs. Rates of innovation and adoption will not slow down in 2017, so we've pulled together the key emerging technology trends to watch and plan for. One thing is for certain in 2017, whether you work in strategy, risk management, operations, start-ups, R&D or marketing, you need to be abreast of the potential of disruptive digital technologies which are no longer purely the realm of the CIO or CTO.
For years, we have been fed an almost constant diet of sci-fi prediction about the consequences of artificial intelligence and our deepening lack of self-reliance. Be it at the hands of vengeful robots, octopedal searcher drones or an omnipresent networked villainous super-brain; we are just fleshy victims waiting to be usurped. Well, the age of artificial intelligence is upon us and predictably, a debate rages on. Ironically, considering the warnings that assail us across the airwaves, one of the realms that is embracing AI is the financial services industry. In 2008, several small technology-oriented startups stole headlines with their move into fully automated investment services.
Artificial intelligence (AI) had a fair bit of air time last year – from tech imitating art in the recreation of Rembrandt's work, to robots outsmarting humans in technical games. Unsurprisingly, some of the biggest names in technology are working hard to establish what AI can do for them, with Facebook, Amazon Google, IBM and Microsoft setting up a partnership to discover just that. So as we settle into 2017, what can we expect from this fascinating field of technology in the next 12 months? The fun projects and headline grabbing tests have done a great job of raising the profile of artificial intelligence, but this year we're going to start seeing some more interesting movement in real-world applications – with gaming, driverless cars and smart cities standing out as three industries that are ready to be boosted by developments in AI. AI in these industries has tended to focus on limited decision trees, which follow'if X then Y' principals.
Ditto Labs, Inc., a pioneer in deep learning announced today that Red Fort Capital led a new round of investment in the vision-as-a-service company. Ditto's vision-as-a-service API can find nearly anything appearing in a photo -- a specific product, brand logo, location, demographic profile -- even subjective measures of sentiment -- in near real time. Ditto's service is a high value AI application for thousands of digital business's. "Humans can no longer keep up: ubiquitous cameras are casting off reams of big data. Today, critical business decisions need computers to act on visual data at massive scale and in real-time," said Red Fort Capital CEO Parry Singh.
Gigaom, the leader in emerging technology research, today announced that it is holding its first annual competition for the AI start-up that delivers the highest ROI to corporate customers. The GAIN competition coincides with the annual conference Gigaom AI Now held in San Francisco, CA, February 15-16th 2017. AI startups are leading the way for bringing positive impacts of AI to many of the world's long-term challenges. "Record number of investments are being made in early stage AI start-ups. The competition will identify which new ventures can deliver the highest ROI to businesses today," explained David Hehman, Gigaom's Start-up & VC editor.
We've written a lot about the convergence of cloud infrastructure, Big Data, and artificial intelligence (AI) this year. Throughout the Software-as-a-Service (SaaS) space, we've seen an inextricable link between these three factors in business intelligence (BI) tools, social listening platforms, customer relationship management (CRM) solutions, or really any industry that's leveraging cloud-based data ingestion and analysis--which is pretty much all of them. Across use cases, we've observed a four-step process. Enterprise businesses gather massive amounts of data by using a portfolio of SaaS apps. They then store that data in the cloud by using a data warehouse or data lake, using data governance to keep data compliant and secure.
There is no doubt that 2016 was a breakthrough year for some of the technologies we have been watching. AI, VR, AR, Chatbots, self-driving cars all took significant leaps forward in terms of their practical applications and adoption, taking many by surprise. It is definitely true to say that the Robots are no longer coming- they are here, and they are taking jobs. Rates of innovation and adoption will not slow down in 2017, so we've pulled together the key emerging technology trends to watch and plan for. One thing is for certain in 2017, whether you work in strategy, risk management, operations, start-ups, R&D or marketing, you need to be abreast of the potential of disruptive digital technologies which are no longer purely the realm of the CIO or CTO.
The buzzwords "Industry 4.0" and "digital business" represent the start of a complex transformational process that will deeply affect industry and society during the next decade. This transformation is based on the convergence of the real (analog) world and the virtual (digital) world by means of machineto- machine (M2M) communication, autonomous systems (for example, robotics) and the Internet of Things (IoT). The German government uses the term "Industry 4.0" as the title of a government project promoting the computerization of traditional industries and the creation of intelligent factories (smart factories) that will be supported by cyberphysical systems and the IoT. The digits "4.0" in Industry 4.0 stand for the fourth industrial revolution: the transition of production from digital processing to fully interconnected processes, products and services. It follows the evolution of production processes for tradable goods from manufacturing to industry production (the first revolution), the move from steam-driven machine production to electricity-driven production (the second revolution) and the shift from analog processing to digital processing and microelectronics (the third revolution).