According to Jim Hare, research vice president at Stamford, Conn.-based Gartner, the push to build and market AI products has been so intense that many vendors have forgotten to do a basic analysis of enterprise needs and use-case scenarios. On July 10, it announced the creation of a new initiative aimed at making AI accessible to workers called PAIR (People AI Research). This follows wide-ranging job cuts at IBM's Global Technology Services division last year, which the company said was the first step in a strategy shift that would redirect IBM towards cloud computing and AI operations, in much the same way Microsoft did a couple of weeks ago. According to Gartner's 2017 AI development strategies survey, more than half of the enterprises survey cited this as a major problem for AI adoption.
Market hype and growing interest in artificial intelligence (AI) are forcing established software vendors to introduce AI into their product strategy, creating considerable confusion in the process, according to Gartner. While there is a widely held fear that AI will replace humans, the reality is that today's AI and machine learning technologies can and do greatly augment human capabilities. Similar to greenwashing, in which companies exaggerate the environmental-friendliness of their products or practices for business benefit, many technology vendors are now "AI washing" by applying the AI label a little too indiscriminately, according to Gartner. To build trust with end-user organisations vendors should focus on building a collection of case studies with quantifiable results achieved using AI.
Microsoft now employs over 7,000 Artificial Intelligence (AI) research scientists and development engineers around the world under Microsoft Research (MSR) Executive VP Harry Shum, who shared the company's vision and strategy during the keynote address. Throughout this event, the company's executives focused "fostering efforts that lie at the intersection of AI, people and society", taking a feel-good approach that may lessen customers' fears of a Hal9000 AI nightmare future, positioning the company as a trusted advisor and provider of practical AI tools, products and services. As an example of the influence and impact of the massive Microsoft Research organization, the company announced a new initiative called AI for Earth, a program aimed at empowering people and organizations to solve global environmental challenges by improving access to AI tools, education and skills to accelerate innovation. This is yet another example where Microsoft has made it possible for enterprises to use, or experiment with, trained neural networks for AI tooling, potentially easing adoption of Microsoft AI technologies in risk-averse, and resource challenged, enterprise IT organizations.
Integrations with core systems like Slack, CRMs and job applicant tracking systems will help Clara keep engagement numbers high while feeding machine learning models new edge cases to improve the quality of the entire product. "Scheduling is different if you're a sales person and your sales team is measured by the total number of meetings scheduled," Nelson told me in an interview. Xuezhao Lan of Basis Set Ventures will be joining the Clara Labs board of directors as the company moves into its next phase of growth. Today's Clara deal is one of the first public deals to involve the recently formed $136 million AI-focused Basis Set fund.
On July 5, Demis Hassabis, co-founder and CEO, DeepMind announced "the opening of DeepMind's first ever international AI research office in Edmonton, Canada, in close collaboration with the University of Alberta." In addition to contributing on the research and education end DeepMind plans to invest in programs to promote "Edmonton's growth as a technology and research hub." It welcomes the DeepMind move as yet another advance toward AI research in the country, which is the goal set by "the federal government's Pan-Canadian Artificial Intelligence Strategy." However, such systems tend to eliminate the need for humans on the jobs rather than increase employment opportunities, and new jobs don't magically open up when old ones are filled by machines.
Artificial intelligence (AI) has become a buzzword, pushing established software vendors to introduce it into their product strategy, "creating considerable confusion in the process", according to IT researcher Gartner Inc. Gartner Inc, on Tuesday, predicted that by 2020, AI technologies will be virtually pervasive in almost every new software product and service and will be one of the top five investment priorities for more than 30% of CIOs, globally. The researcher said that in May 2017, the term artificial intelligence was the seventh most popular term on gartner.com, The term did not feature in top 100 search terms back in January 2016. "AI offers exciting possibilities, but unfortunately, most vendors are focused on the goal of simply building and marketing an AI-based product rather than first identifying needs, potential uses and the business value to customers," said Jim Hare, research vice president at Gartner. Even as companies across the globe are currently seeking AI solutions to enhance decision making and process automation, Hare suggests vendors to use the term'AI' wisely in sales and marketing materials and "be clear what differentiates your AI offering and what problem it solves," to avoid confusion and make the most of AI technologies.
To give you a little more context -- and paraphrasing Alex's post -- we have entered the third wave of AI startups. The wave of applied AI companies. A second wave followed and consisted of companies building machine learning infrastructures. These startups did build some commercial traction, but most of them were also acquired before reaching scale.
VentureBeat: What if Google, Amazon, and Facebook had started with AI algorithms a long time ago, before they got hip to this subject more recently? Relan: You had all this irrelevant content, and the core strategy of Facebook in the early days was simply to let the community sort it out, until it reached a breaking point where there was so much spam from FarmVille on Facebook -- I remember meeting Mark Zuckerberg in 2010, and at this point he literally said, "I hate this." The bad content 10 years ago was game spam. The notion of combining humans with AI, whether it's at Facebook or -- at Google it's actually very interesting, because the search engine runs completely on servers, and the AI engine they've added to the search system is also completely running on servers.
The real goal of AI in games is to simulate intelligent behavior, providing the player with a believable challenge-a challenge that the player can then overcome. More complex systems require some means of perceiving the AI's environment, a record of player actions, and some means of evaluating the success of previous decisions. Entity pull systems work best for games with simple entities. A good example of a rules-based system is a Black Jack dealer (either video Black Jack or real Black Jack).
When AI traders do make mistakes, they are able to learn from them at an exceptionally fast rate. What takes traders months to learn, an artificial intelligence program can learn in mere moments. Still, AI's outperforming traditional quantitative firms cannot be ignored. "Computers will have an edge in processing large amounts of economic data, but may struggle with the more qualitative judgments Mr Buffett has excelled in such as judging the character of a chief executive or the durability of a brand."