Machine learning, artificial intelligence (ML & AI) and big data form up a new niche area that is seeing a fast-paced growth rate in India. To clarify terminologies for a layperson, AI is basically all about mimicking human intelligence in machines, ML is a sub-set of AI and is about techniques that enable these machines to continuously learn on their own through data and perform a desired set of processes. Big Data analytics is about extracting huge data and observing unanticipated patterns from the same, while ML uses the same to provide incremental data/information to help the machine learn on its own. Data science and big data industry in India is growing at 33per cent CAGR (Compounded annual growth rate) and stood at $2.71 Billion in 2018. While the Finance & Banking industry leads the share in the analytics market, travel-hospitality and healthcare saw the fastest growth in recent years, in terms of analytics-use.
Bottom Line: Machine learning is enabling threat analytics to deliver greater precision regarding the risk context of privileged users' behavior, creating notifications of risky activity in real time, while also being able to actively respond to incidents by cutting off sessions, adding additional monitoring, or flagging for forensic follow-up. A commonly-held misconception or fiction is that millions of hackers have gone to the dark side and are orchestrating massive attacks on any and every business that is vulnerable. The facts are far different and reflect a much more brutal truth, which is that businesses make themselves easy to hack into by not protecting their privileged access credentials. Cybercriminals aren't expending the time and effort to hack into systems; they're looking for ingenious ways to steal privileged access credentials and walk in the front door. According to Verizon's 2019 Data Breach Investigations Report, 'Phishing' (as a pre-cursor to credential misuse), 'Stolen Credentials', and'Privilege Abuse' account for the majority of threat actions in breaches (see page 9 of the report).
Here are 5 significant artificial intelligence trends to look forward to that will affect myriad industries on an international scale led by giant tech companies that are now investing huge sums in artificial intelligence research. Last year, implementations of AI rose significantly in so many platforms, tools and applications around the world, impacting healthcare, education and other industries as more and more people are opting for e-solutions based on AI and machine learning. Then there's the automotive industry with self-driving cars, the agricultural sector opting for intelligent robots to tackle the sowing as well as insecticide spraying on crops; the list goes on. As tech industry giants, including Google, Facebook and Amazon, invest billions now in AI and machine learning research, let's explore how 2019 is unfolding on this front. Major chip manufacturers including Intel, Nvidia, AMD and ARM aim to produce AI-powered chips to speed up the operations of applications that run on AI.
HONG KONG (Reuters Breakingviews) - Artificial intelligence doesn't hate you, prominent researcher Eliezer Yudkowsky wrote, "nor does it love you, but you are made of atoms which it can use for something else". This sets the scene for Tom Chivers' fascinating new book, which borrows its title from the quote, on why so-called superintelligence should be viewed as an existential threat potentially greater than nuclear weapons or climate change. The "strange, irascible and brilliant" Yudkowsky is a central figure throughout the book. His early musings on the potential and dangers of artificial intelligence during the mid- to late-2000s gave birth to the Rationalist movement, a loose community dedicated to AI safety. Chivers, a former science journalist with Buzzfeed and the Telegraph, offers a meticulously researched investigation into who the Rationalists are, and more importantly why they believe humanity is fast approaching an inflection point between "extinction and godhood".
We live in a world that is becoming more personalized every day. Consumers have come to expect experiences that are tailored for them -- especially when it comes to engaging with brands. When you open your Uber app, it now suggests your home address; online shopping is increasingly personalized, and, of course, so is advertising. You expect to see ads that reflect your interests and buying patterns and, in fact, are more likely to engage with those ads.We have artificial intelligence (AI) to thank for our increasingly personalized world. As the demand for personalization increases, so too does the buzz around AI. AI is a term that is becoming ubiquitous -- and potentially overused -- as an umbrella term relating to any action a machine takes based on a set of rules in order to mimic human intelligence.
Remember the time when tech companies were cool? Once upon a time, Silicon Valley was the jewel in the American crown, a magnet for high IQ – and predominately male – talent from all over the world. Palo Alto was the centre of what its more delusional inhabitants regarded as the Florence of Renaissance 2.0. Parents swelled with pride when their offspring landed a job with the Googles, Facebooks and Apples of that world, where they stood a sporting chance of becoming as rich as they might have done if they had joined Goldman Sachs or Lehman Brothers, but without the moral odium attendant on investment backing. I mean to say, where else could you be employed by a company to which every president, prime minister and aspirant politician craved an invitation?
Machine learning and Artificial intelligence have taken over data centers by storm. As racks begin to fill with ASICs, FPGAs, GPUs, and supercomputers, the face of the hyper-scale server farm seems to change. These technologies are known to provide exceptional computing power to train machine learning systems. Machine learning is a process that involves tremendous amounts of data-crunching, which is a herculean task in itself. The ultimate goal of this tiring process is to create applications that are smart and also to improve services that are already in everyday use.
After decades of a heavy slog with no promise of success, quantum computing is suddenly buzzing! Nearly two years ago, IBM made a quantum computer available to the world. The 5-quantum-bit (qubit) resource they now call the IBM Q experience. It was more like a toy for researchers than a way of getting any serious number crunching done. But 70,000 users worldwide have registered for it, and the qubit count in this resource has now quadrupled.
Artificial intelligence in transportation helps the transportation companies to ensure public safety for their service. Artificial Intelligence in transportation makes use of various concepts like deep learning, computer vision, and context awareness to know the way the drivers handle their resources. The global artificial intelligence in the transportation market is experiencing high demand due to the increasing popularity of the autonomous vehicle. Various organizations are using AI in transportation solutions for data collection and decision making. The growing use of autonomous vehicles, and need to control the operational costs are the major factors that are expected to support the growth of artificial intelligence in transportation market whereas failure in performance is the major factor that is expected to slow down the growth of this market.