The artificial intelligence technology is deployed by cybersecurity firms in an effort to keep pace with the evolution of cyberattacks, as machine learning algorithms are able to improve predictability the more it is used. But according to Guy Caspi, CEO of cybersecurity company Deep Instinct, machine learning is no longer enough in an age of unprecedented evolution and volume of cybercrime. Part of that is because machine learning relies on only two or three algorithms; deep learning deploys tens of algorithms, and complex math. But the ongoing evolution of corporate cybercrime means cybersecurity companies may no longer be able to afford relying solely on machine learning.
JP Morgan's recently released 280-page report Big Data and AI Strategies – Machine Learning and Alternative Data Approaches to Investing paints a picture of a future in which alpha is generated from data sources like social media, satellite imagery and machine-classified company filings and news releases. Alpha generation has always been about information advantage: having access either to uncommon insights gained through ingenuity, or common insights acted upon before everyone else. JP Morgan's Contract Intelligence System processes the paperwork for financial deals that previously took tens of thousands of human hours annually. Retiring old systems and moving to integration and data-centricity will require investment and some decent amount of vision, but it will result in future opportunities and cost savings: both from automation and from the ability of such systems to better take advantage of rapidly accelerating advancements in AI, which will require smart data collection, processing and management.
There is growing polarization of labor-market opportunities between high- and low-skill jobs, unemployment and underemployment especially among young people, stagnating incomes for a large proportion of households, and income inequality. Challenges in labor markets are growing, household incomes in advanced economies have been stagnating, and there are increasing skill gaps among workers. The decline is due in part to the growth of corporate profits as a share of national income, rising capital returns to technology investments, lower returns to labor from increased trade, rising rent incomes from home ownership, and increased depreciation on capital. In a McKinsey survey of young people and employers in nine countries, 40 percent of employers said lack of skills was the main reason for entry-level job vacancies.
Microsoft Corp. MSFT recently announced the launch of Microsoft Research AI lab. It will focus on obstacles faced in the field of artificial intelligence (AI). Zacks Rank Currently, Microsoft holds a Zacks Rank #2 (Buy). You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here.
American technology giant Google has acquired Bangalore-based artificial intelligence (AI) firm Halli Labs for an undisclosed sum. "We will be joining Google's Next Billion Users team to help get more technology and information into more people's hands around the world. A Google spokesperson said, "We are excited that the Halli Labs team is joining Google. Some of the acquisitions by Google in AI include firms such deep learning and neural network startup DNNresearch from the computer science department at the University of Toronto in 2013; British company DeepMind Technologies in 2014 for $600 million; visual search startup Moodstock, and bot platform Api.ai last year.
"Halli Labs is applying modern ML techniques to old problems and domains to help technology march on in its timeless purpose-- that of giving superhuman powers to all of us humans in letting us do whatever we want to do, better," the post read. Pankaj Gupta, an Indian Institute of Technology, Delhi, and Stanford University alumnus, is the founder of Halli Labs. He is "building products based on applied ML in speech recognition and NLP domains," Jhala's Linkedin profile said. "Welcome Pankaj and the team at Halli Labs to Google.
NEW DELHI: American technology giant Google has acquired Bangalore-based artificial intelligence (AI) firm Halli Labs for an undisclosed sum. "We will be joining Google's Next Billion Users team to help get more technology and information into more people's hands around the world. A Google spokesperson said, "We are excited that the Halli Labs team is joining Google. Some of the acquisitions by Google in AI include firms such deep learning and neural network startup DNNresearch from the computer science department at the University of Toronto in 2013; British company DeepMind Technologies in 2014 for $600 million; visual search startup Moodstock, and bot platform Api.ai last year.
Today, Toyota announced the launch of Toyota AI Ventures, a new venture capital subsidiary focused on startup tech companies working on artificial intelligence. The fund has received an initial $100 million from the Toyota Research Institute (TRI), an AI-, robotics- and autonomous car-focused initiative created in 2015. AI Ventures will direct its investments towards AI, robotics, autonomous vehicles and data and cloud technology. Toyota joins a number of other companies forming AI-focused venture capital funds including Baidu, which established theirs last year, and Google's Gradient Ventures, which was announced today.
A featured portion of this 19th annual M&A conference features Artificial Intelligence (AI) and Machine Learning (ML) experts sharing their experience gained from research, consulting, and analysis of more that 20,000 deals offering game-changing tech innovations that will change how deal making is done forever. Dr. Kiran Garimella, co-founder and columnist, is a former Global CIO and Chief Architect at GE, VP for Business Process Management at Software AG, and an expert in building Centers of Excellence. Fueled by artificial intelligence and machine learning, the platform helps advisors accelerate deals and streamline processes. In addition, Evan Eichorn, Senior Account Director, will add valuable insights from D&B Hoovers, combining the best of the former Hoovers solution, insights-rich Dun & Bradstreet data, and the robust Avention OneSource platform – providing sales, marketing, research, and procurement professionals with the edge they need to make informed decisions and stay one step ahead of the competition.
A new study has found it's actually surprisingly easy to model how humans make them, opening a potential avenue to solving the conundrum. In the face of such complexities, programming self-driving cars to mimic people's instinctive decision-making could be an attractive alternative. For a start, building models of human behavior simply required the researchers to collect data and feed it into a machine learning system. By basing the behavior of self-driving cars on a model of our collective decision making we would, in a way, share the responsibility for the decisions they make.