We've been told that there is nothing to worry about artificial intelligence, robots and technology. New technologies will only replace mundane, repetitive jobs and free up workers to do more meaningful work, claims the media and top management consulting firms. Last week, the House Financial Services Committee's Task Force on Artificial Intelligence conducted a meeting with university academics and Wall Street financial services professionals to discuss the impact of AI on trading, robo-advisory, market surveillance and other activities within the financial services sector. To set the tone, the report by Wells Fargo predicting 200,000 banking jobs in the U.S. will be lost over the next decade--due to the introduction of new technologies--was cited by the chairman of the AI Task Force, Rep. Bill Foster (D-Ill). According to Marcos Lopez de Prado, the former head of machine learning at AQR Capital Management, algorithms in electronic markets have already automated the jobs once dominated by thousands of traders.

The modern world is changing more and more quickly with each passing year. If you don't pay attention to new changes or keep up the pace, it's easy to fall behind the times (and the market) while other companies beat you to the punch. To keep abreast of current changes – at least at a level of basic understanding. Adding to that, if you can't understand the buzzwords others are using in conversation, it's much harder to look smart while participating in that conversation. In this post, we're going to give you the 10 IT & technology buzzwords you won't be able to avoid in 2020 so that you can stay poised to take advantage of market opportunities and new conversations alike. The first in our definitive rundown of tech buzzwords 2020 is computer vision. Exciting and futuristic, the concept of computer vision is based on computing devices or programs gaining the ability to extract detailed information from visual images. In a computing context, 'vision' involves systems that can identify items, places, objects, or even humans from visuals mediums – images caught by a camera or sensor.

As 2019 draws to a close and a new year and a new decade are nearly upon us, we're looking back at the year's biggest AI innovations. Companies have applied artificial intelligence and machine learning to everything from enhancing the customer experience to revolutionizing medicine. Here's a closer look at key innovations in AI that made a splash in 2019 and set the stage for future innovation in 2020 and beyond. AI innovations and machine learning have made significant leaps forward in the financial industry. According to a Deloitte report, "AI leaders In financial services: Common traits of frontrunners in the artificial intelligence race", AI tools are reshaping many aspects of financial services and the way we manage our money.

When it comes to contracts, every business learns to deal with several important contractual facts of life. One is that contracts need to accurately protect the company's business interests while adhering to acceptable legal practices and regulatory requirements in relevant jurisdictions. Another is that contracts must be faithfully administered in order to serve their basic business functions. Finally, contract management costs a lot. It is the cost of creating and administering contracts inefficiently.

Observe.ai, an artificial intelligence-based startup that focusses on voice conversations for customer service, has raised $26 million (approximately Rs 184.16 crore at current exchange rates) in its Series A funding round from a clutch of investors. California-based venture capital firm Scale Venture Partners led the investment round, Observe.ai said in a statement. Other investors that participated in the round include Nexus Venture Partners, Steadview Capital, 01 Advisors and Emergent Ventures. The company said it will use the funds to expand its US and India teams, and will also accelerate its product development. Swapnil Jain, co-founder and chief executive officer at Observe.ai, said the investment will fuel the firm's mission to elevate agent performance through AI-based coaching and insights The latest investment takes the total funding raised by Observe.ai

I'm in the middle seat of a Chrysler Pacifica minivan, heading north on Dobson Road in Chandler, Arizona, when I notice we may have taken a wrong turn. Under normal circumstances, I would just lean forward and ask the driver for an explanation. There is, after all, no driver to ask. Last October, Alphabet's self-driving subsidiary Waymo emailed its customers in the suburbs of Phoenix to let them know that "completely driverless Waymo cars are on the way." For several years, Waymo has offered its autonomous taxi service to a small group of people, but the rides typically included a safety driver behind the steering wheel. Now, Waymo is saying more of those rides will take place sans safety driver, a sign that the company is growing confident in the accuracy of its technology.

Like Google, Uber, and countless other startups and tech giants, Lyft is developing cars it hopes will someday ferry passengers sans driver -- a task that's easier said than done. In a Medium post published this morning, Lyft's Level 5 team -- the division devoted to autonomous vehicle (AV) research and development -- laid out a few of the challenges its engineers have encountered to date, while pulling back the curtains on solutions and general progress. Picture this: A car driving down a freeway encounters another car cutting across multiple lanes to make an exit. Preventing a collision would require the first car to slow down, but just how dramatic should that slowdown be? Lyft's self-driving prototypes tap what the company calls a "human-inspired" planning approach to determine this.

IMAGE: Schematic diagram of the proposed multichannel deep neural network model analyzing multiscale functional brain connectome for a classification task. OAK BROOK, Ill. - Deep learning, a type of artificial intelligence, can boost the power of MRI in predicting attention deficit hyperactivity disorder (ADHD), according to a study published in Radiology: Artificial Intelligence. Researchers said the approach could also have applications for other neurological conditions. The human brain is a complex set of networks. Advances in functional MRI, a type of imaging that measures brain activity by detecting changes in blood flow, have helped with the mapping of connections within and between brain networks.

INDIA'S government wants to build one of the largest facial recognition systems in the world. But critics warn it could be a blow to citizens' rights. The country's National Crime Records Bureau (NCRB) has invited bids to develop a nationwide facial recognition system that can automatically identify people from CCTV feeds and images uploaded through a mobile app. The NCRB says it will help police catch criminals, find missing people and identify dead bodies. The technology works by scanning the structure of people's faces and comparing the results …

The ADAPT Centre at Trinity College Dublin has received funding to hire a start-up founder to spin-out the business start-up Darwin & Goliath http://darwingoliath.com in the field of recommendations-as-a-service. The position is to be filled with a product manager, machine-learning engineer, software engineer, or software architect. The person is expected to work together very closely with the project lead and Business Administrator. Both will be responsible for developing a recommender-system as-a-service that uses unique machine-learning technology, which is based on the research of Professor Joeran Beel who is the project lead. This position is flexible in the responsibilities and open to focus more on either software engineering / machine-learning or on the architectural and product management part.