Between fiddling our fingers on the tiny buttons of our TV remote and scrolling through endless menus to find something worth watching and talking to a smart assistant via your remote or your smart TV to find a movie based on your interests, which one of them sounds more absurd? The concept of machine-human intelligence coined during the mid-twentieth century and increasingly popular in the sci-fi movies during the early days, has long become a reality and is unfolding more and more potential areas of its application with each passing day. Instead of having incertitude regarding the notion of pursuing AI, most of the companies are now asking themselves the question of how should they pursue AI as they try to unlock the hidden potentials it can provide, and the creative and informatics industries are no exception to the trend. The highly packed and ambitious media industry is always on the hunt for new ways to compete with the firms adopting newer technologies to stay in pace with rising technological transformation. Leading this rapid transformation are the horses of efficient workflow support, content distribution management and revenue growth support.

Sharing a similar viewpoint with these legends, Kevin Kimber, a well-known financial expert in business circles, also believes that AI can specifically power financial applications to streamline processes, connect data between finance and back-office operations with the front office and commercial function and in doing so increase a company's revenue. Case in point--Rimilia, a Fintech solutions provider with Kevin as its CEO, is a perfect example for intelligent cash application, credit management, and collections in the finance industry. Today, the modern corporation has unique opportunities to automate in many areas that previously weren't possible and with the maturity of a small number of super-intelligent applications and their development within the finance industry, now is the time for companies to take advantage and drive change. Current day finance technology providers need to not only understand the complexities that run across the financial estate but also assist companies in carefully navigating forward. With an in-depth knowledge of these complexities and professional expertise to successfully get around them, Kevin Kimber, CEO of Rimilia, knows the opportunities companies have.

Most stocks, no matter how well they perform, eventually hit a rough patch that can serve as an excellent entry point for opportunistic investors. That may be the situation Baidu (NASDAQ:BIDU) currently finds itself in. Between the U.S.-China trade war and a decelerating economy, the internet tech giant has been feeling the pressure from multiple angles. As a result, Baidu's shares are down by about 50.7% from a year ago. Further, Baidu's valuation is down as well, trading at just 7.90 times past and 15.57

The U.S. Department of Energy recently announced the funding of another set of quantum science-driven research proposals, including that of Sau Lan Wu, Enrico Fermi professor of physics and Vilas Professor at the University of Wisconsin – Madison. With the funding, Wu and her collaborators seek to tap into the power of quantum computing to analyze the wealth of data generated by high energy physics experiments. The title of Wu's DOE approved project is: "Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware". Wu, a member of the Chicago Quantum Exchange (CQE) and Wisconsin Quantum Institute at UW–Madison who conducts her research at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland, was one of only six university-based investigators – those outside of National Labs – to be awarded the DOE quantum funds for particle physicists. "The ambitious HL-LHC program will require enormous computing resources in the next two decades," says Wu. "A burning question is whether quantum computers can solve the ever-growing demand for computing resources, and our goal here is to explore and to demonstrate that quantum computing can be the new paradigm."

The pace and scale of medical and scientific innovation is transforming the biopharma industry. The need for better patient engagement and experience is spurring new business models. Data generated, captured, analysed and used in real time by innovative medical devices is biopharma's new currency. A key differentiator for companies is the extent to which they are able to generate insights and evidence from multiple data sources. Consequently, digital transformation is a strategic imperative. This report outlines how artificial intelligence-enabled technologies will impact the biopharma value chain and accelerate biopharma's digital transformation. Although there is a high level of innovation in the industry, biopharma companies are facing a complex and challenging environment due to increased competition and R&D cycle times, shorter time in market, expiring patents, declining peak sales, pressure around reimbursement and mounting regulatory scrutiny. As we have shown in our series of reports on'Measuring the return from pharmaceutical innovation', these factors are contributing to an alarming decline in the projected return on investment that large biopharma companies might expect to achieve from their late-stage pipelines, threatening their long-term futures.1 Digital transformation could provide a lifeline to biopharma research and development (R&D) and help reverse this trend. Digital transformation will also impact beyond R&D, as companies look to improve their operational performance, productivity, efficiency and cost-effectiveness across the entire biopharma value chain (see figure 1). Digital transformation will also impact business models, the development of new products and services, and how companies engage with health care professionals, patients and other customers. Ultimately, digital transformation is the next step in the evolution of biopharma companies.

A vast new research survey on Future Systems from Accenture (NYSE: ACN) sheds important light on the enormous impact that technology investment and adoption have on a company's financial performance and most notably, the mindsets and behaviors of companies that are industry leaders. The new research, titled: "Full Value. How to scale innovation and achieve full value with Future Systems," provides insights on how to scale innovation and achieve full value of technology investments, builds on Accenture's initial Future Systems report launched last year, and is based on a survey of more than 8,300 organizations across 20 industries and 22 countries. It is designed to help companies understand and close the innovation achievement gap – defined as the difference between potential and realized value from technology investments. The Future Systems research is Accenture's largest enterprise IT survey ever conducted and includes measures of both mature and emerging technologies such as artificial intelligence (AI), blockchain, and extended reality.

Tokyo-based AI Medical Service Inc., which is developing endoscopic software powered by artificial intelligence, announced today that it has raised $42.9 million in a Series B round. Japan's Globis Capital Partners, World Innovation Lab (WiL) out of Palo Alto and Sony Innovation Fund by IGV (Innovation Growth Ventures), and others participated in the financing. Combined with the company's last raise of $9 million in August 2018, AI Medical Service has now brought in about $57 million in venture funding since its inception in September 2017. In its own words, the company "develops AI technology that brings together the wisdom of Japanese endoscopic specialists and supports endoscopic examinations of gastrointestinal organs, such as the esophagus, stomach, small intestine and large intestine." Its goal is to more quickly and efficiently diagnose gastric cancer.

Deal making landscape in the artificial intelligence (AI) tech space during 2014–2018 was dominated by global tech giants, according to GlobalData. Of the top five acquirers, four were based out of the US, with Ireland-based Accenture being the only exception in the list. The four US-based companies–Facebook, Microsoft, Apple and Splunk–collectively accounted for 30 acquisitions in the AI tech space during 2014–2018, whereas Accenture acquired six companies in this area during the period. Aurojyoti Bose, Financial Deals Analyst at GlobalData, said, "Technology companies have been the dominant deal makers in the AI space. However, with AI making inroads into diverse sectors, the buyer universe in expanding and the space is also attracting investments from non-technology companies."

Alteryx, a publicly traded analytics company, announced this morning that it has acquired Feature Labs, a machine learning startup that launched out of MIT in 2018. The company did not reveal the terms of the deal. Co-founder and CEO Max Kanter told TechCrunch at the time of the launch the company had been based on research at MIT that looked at how to automate the creation of machine learning algorithms. "Feature Labs is unique because we automate feature engineering, which is the process of using domain knowledge to extract new variables from raw data that make machine learning algorithms work," Kanter told TechCrunch in 2018. It is precisely this capability that appealed to Alteryx .