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) …
A Bangalore-based startup is claimed to have become the first company in the world to successfully complete a difficult 20-part challenge in Artificial Intelligence created by Facebook in 2015. Using a unique approach, DataVal Analytics successfully completed all 20 tasks of the test, known as the (20) QA bAbi Tasks, with 100 per cent accuracy. The test, hosted by Facebook AI Research (FAIR), assesses the ability of AI-based programs to perform text understanding and reasoning. According to a media release, DataVal Analytics, which has its head office in Chicago but operations office in Bangalore, has been founded by veterans from the Indian Army – Lt Col Shashi Kiran (Veteran) and Lt Col Naveen Xavier (Veteran). The team is mentored by the leading entrepreneur, innovator, policy maker and development thinker, Sam Pitroda as chairman.
Facebook and Micron are among the favorite ways to play the boom in artificial intelligence, according to top technology analysts. The analysts were identified by looking at the average return of their recommendations and their success rate in those calls, as tracked by TipRanks, a Wall Street analyst database. Here are five favorite AI stocks recommended by the best-performing technology analysts. In 2017, Microsoft changed its strategy from a "mobile-first and cloud-first world" to "an intelligent cloud and an intelligent edge infused with AI." And this strategy shift seems to be paying off.
Difficult times for operators call for questioning old orthodoxies to win. For the better part of a decade, telecom companies have suffered through declining revenues, cash flow, and return on investment just as tech companies like Google, Facebook, Amazon, and others have mushroomed by building their businesses on the operators' own infrastructure. While these tech visionaries have enjoyed well over $1 trillion in combined market-cap growth by innovating and thinking differently and adeptly, telecom companies have tried to compete by implementing the same old survival tactics: cutting costs, reducing the workforce, and timidly entering into new business adjacencies. The trouble is that playbook no longer applies. It's time the telecom companies embrace this new reality and rethink the key orthodoxies that have shaped their industry since the first phone call was made about 140 years ago.
And here comes an AI bot developed by stock analysts at Wells Fargo Securities. According to their note to clients on Friday, reported by Bloomberg, the AI bot promptly slapped a "sell" rating on Google and Facebook. Last month, a group led by Ken Sena, head of Global Internet Analyst at Wells Fargo Securities, introduced this "artificially intelligent equity research analyst" or AIERA. This is in blatant contradiction to Wall Street's human hype machine, which has 42 "buy" recommendations out of 47 ratings on Facebook, according to Bloomberg, and 34 "buy" recommendations out of 41 ratings on Alphabet.
If Alphabet, Amazon and Facebook (along with Berkshire Hathaway) paid shareholder dividends at the 2.37% average yield of other S&P 500 companies that do so, it would shake out another $32.2 billion for investors, according to Howard Silverblatt, senior index analyst at S&P Dow Jones Indices. How to choose a smart speaker More: Here's one way Google envisions search changing for you But don't expect these tech companies to pay a dividend anytime soon. "During the 1990s, tech didn't typically pay dividends and they drove the stock market back then," said Kim Forrest, senior equity analyst at Fort Pitt Capital. The S&P tech sector had a dividend yield of 1.36% during the third quarter, the lowest of the 11 sectors and well below the overall S&P 500 of 1.97%, according to Silverblatt.
BCS Technology, a Global IT company headquartered in Australia providing end to end solutions in big data and analytics, announced the launch of their chatbot solution -- Interactive Social Airline Automated Companion (ISAAC) built on Cloudera's modern platform for machine learning and analytics optimized for the cloud -- Cloudera Enterprise. The solution combines the use of modern big data analytics technologies and natural language processing (NLP) by leveraging Microsoft's LUIS framework and the Cloudera Enterprise platform. "With Cloudera's machine learning and advanced analytics technology at the core of ISAAC, businesses can now use data to gain valuable insights, make accurate business decisions faster and deliver better products and services to enhance their customers' experiences. With the exponential growth of BCS and big data, a new subsidiary named ML Labs has formed, specialising in providing machine learning and deep learning algorithm solutions to clients looking to begin their journey through big data and analytics.
My bleak forecast does not stem from the notion behind the common fintech (financial technology) and insurtech (insurance technology) industry pitch that they will change their respective industries with innovation and better customer experiences, although I firmly believe that some of the startups will cause significant pain to the incumbents and will indeed change their respective industries. These organizations will use their customers and employees to sell banking and insurance solutions, and the big financial institutions will become at best dumb pipes. What is terrifying to imagine is a situation in which tech giants or other big companies provide financial service solutions at or below production costs. The new competitors would not need to earn money and could even afford to lose money in offering financial solutions if these features entice customers and new potential clients to use the companies' core offerings.
Recently, analyst Trip Chowdhry of Global Equities Research wrote in an investor note that Wal-Mart Stores (NYSE:WMT) will ramp up its focus on deep neural networks for its OneOps cloud business and that the retailer will tap NVIDIA's (NASDAQ:NVDA) graphics processing units (GPUs) to make this happen. Deep neural networks, and the broader deep learning segment, are part of a growing artificial intelligence market. Additionally, NVIDIA said in its second-quarter fiscal 2018 report that it forged new partnerships with Microsoft, Google, Tencent, IBM, Baidu, and Facebook to help them bring new deep learning and artificial intelligence services online. Aside from NVIDIA's deep-learning total addressable market, adding more of these customers is important, because the company's data center revenue segment (which includes GPU sales for deep-learning technologies) is becoming a larger part of the business.
CrowdFlower, a company that helps customers build AI systems by providing them with training data, announced today that it's getting into the business of helping companies implement machine learning. Even as President Donald Trump assails news coverage of his administration, his election has reminded America's citizenry of the value of a vigorous and[…] Bark.us saves teens' lives by using AI to analyze their online activity The analysis of the words people use in chat environments can help businesses make money and improve the customer service experience for consumers. At Bark.us, however, analysis of 500 million messages has so far helped save the lives of 25 kids […] How Walmart uses AI to serve 140 million customers a week Old dogs can always learn new tricks, provided they are smart enough and have the right tools. Founded in 1962 -- a generation or so before ecommerce giants like Amazon -- Walmart has 11,700 stores and 140 million weekly shoppers in 28 countries around the world.
Facebook announced today that it has started using neural network systems to carry out more than 4.5 billion translations that occur each day on the backend of the social network. Translations carried out with recurrent neural networks (RNNs) were able to scale with the use of Caffe2, a deep learning framework open-sourced by Facebook in April. We got an efficiency boost of 2.5x, which allows us to deploy neural machine translation models into production," the Caffe2 team said in a blog post. "To remedy this and build our neural network systems, we started with a type of recurrent neural network known as sequence-to-sequence LSTM (long short-term memory) with attention," software engineers Necip Fazil Ayan, Juan Miguel Pino, and Alexander Sidorov, members of Facebook's Applied Machine Learning team, said in a blog post.