RPA is Creating a Billion-Dollar Market While No One is Looking - RTInsights


RPA, which covers AI and machine learning capabilities used to handle high-volume, repeatable tasks that once needed humans, is coming. RPA stands for Robotic Process Automation, but don't be confused: it doesn't refer to R2D2, or any of the Kiva robots scurrying around the Amazon warehouse. RPA is language that covers the broad use of software with artificial intelligence (AI) and machine learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform. Given the innovation it represents and the pain points it satisfies, RPA is quickly making its way towards a billion dollar revenue market. In recent months alone, leading startups in the space have raised over $300 million for their RPA systems.

Microsoft's AI Platform Gets A Big Boost With Bonsai Acquisition

Forbes Technology

Microsoft has announced that it is acquiring Bonsai – an AI startup focused on reinforcement learning – to expand its AI offerings. This move helps Microsoft in expanding its portfolio to autonomous systems and industrial control systems. Bonsai, an artificial intelligence startup based in Berkeley, California, aims to democratize AI by making the technology accessible to business decision makers. It is abstracting the complexity involved in implementing reinforcement learning. Mark Hammond, the co-founder, and CEO of Bonsai is not new to Microsoft.

Microsoft just bought an AI startup to try to make the technology easier to use in the real world


Bonsai aims to make artificial intelligence technology easier to use in the real world. Microsoft has agreed to acquire Bonsai, a startup focusing on the hot field of artificial intelligence. Bonsai will become part of Microsoft's commercial AI offering through its own Project Brainwave foundation and its Azure cloud computing service, said Gurdeep Pall, Microsoft's corporate vice president of business AI, in a blog post Wednesday. "Bonsai has achieved some remarkable breakthroughs with their approach that will have a profound impact on AI development," he said. AI -- especially areas called machine learning and neural networks -- is an immensely important development in computing.

WalkMe buys Israeli machine learning co DeepUI - Globes


Israeli website navigation and digital adaptation platform company WalkMe today announced that it has acquired Israeli startup DeepUI, a company in stealth mode that has developed a patented machine learning technology to understand any business software at the graphical user interface (GUI) level, without the need for an application programming interface (API). No financial details were disclosed. The company has 600 employees with over 300 in Israel. DeepUI is WalkMe's third acquisition since the company was founded in 2011. WalkMe acquired native mobile AI startup Abbi in January 2017, and visual analytics startup Jaco in April 2017.

Artificial Intelligence: Heidrick & Struggles' Newest Specialty Practice


Clients across all industry sectors will be served by a new specialty practice in Artificial Intelligence (AI) at Heidrick & Struggles (Nasdaq: HSII), a premier provider of executive search, leadership assessment and development, organization and team effectiveness, and culture shaping services globally. Machine learning and other advanced forms of AI can help companies in every sector move beyond process automation that has helped drive efficiency and growth. Integrating and optimizing adaptive changes made possible by AI can provide massive competitive advantage. But there is a critical shortage of leaders with the ability to apply a deep understanding of AI to completely rethink and transform an organization's business model. Led by Ryan Bulkoski, a San Francisco-based partner, Heidrick & Struggles' AI Specialty Practice will help clients identify and develop senior talent needed to bring the power of emerging technologies to their business.

Oracle aims to put voice interfaces on Fusion ERP, HCM apps


Oracle CTO Larry Ellison said that the company is enabling its Fusion ERP and Fusion HCM interfaces to support voice services such as Amazon Alexa. You know Alexa for Business is going to loom large in the enterprise when Ellison, who is a tad obsessed with beating Amazon Web Services, is mentioning the digital assistant. Speaking on Oracle's fourth quarter earnings conference call, Ellison said the company has just about completed an effort to meld all of its software-, platform- and infrastructure-as-a-services in one data center. "This consolidation of all 3 categories of cloud services, SaaS, PaaS and IaaS, into a single standard data center, allows us to share assets while giving significant -- while giving a significant economies of scale. As a result, we expect continued expansion of our cloud margin," said Ellison.

AI Weekly: Google's research center in Ghana won't be the last AI lab in Africa


This year, we have seen an acceleration of Silicon Valley tech giants opening AI research labs around the world as they seek to gain traction among researchers and fulfill their global ambitions. In the past six months or so, Google brought labs to China and France, Facebook opened labs in Pittsburgh and Seattle, and Microsoft announced plans to open labs near universities in Berkeley, California and Melbourne, Australia. This trend shows no signs of slowing down. Last month, Samsung announced labs in Cambridge, Moscow, and Toronto. This week, Nvidia announced plans to open a new lab in Toronto, while Google shared plans to open a lab in Accra, Ghana, Google's first in Africa and perhaps the first of any tech giant in Africa.

CGG: Increasing E&P efficiency with the cloud and machine learning


The IT industry is experiencing an important transformation as companies invest in new technologies to drive growth and innovation. This trend is strongly reflected in our industry as E&P companies deal with enormous amounts of legacy, and increasing volumes of new data along with the expense and complexity of software to analyze and interpret this information. Challenges faced include operational efficiency, increasingly short project cycle times, communicating with a regional or global workforce, data silos, legacy software and restricted resources. Due to the industry's dynamics and its need for flexibility and information security, the cloud is increasingly seen as a viable and practical solution for the oil & gas industry, particularly now that Cloud service providers are building security into their software development processes. Security of data in the Cloud is often better today than in company's own networks.

This Research Startup Raises $13.1M in Funding to Give Doctors Access to An Unprecedented Amount of Medical Knowledge


The advent of machine learning has provided the healthcare industry with an unprecedented increase in knowledge. Data-driven databases now enable doctors to give patients accurate diagnosis earlier on that ever before. OWKIN is a machine learning platform for medical research. The company hopes that its predictive analysis platform will enable doctors to effectively understand patient and tumor heterogeneity. AlleyWatch spoke with Cofounder and CEO Thomas Clozel to learn about the company's latest technological advancements in medical research and its latest round of funding, which brings the total funding raised to $18M over two funding rounds for the startup founded in the fall of 2016.

AI Pioneer Wave Computing Acquires MIPS Technologies

Forbes Technology

Wave Computing, a Silicon Valley AI startup specializing in data flow processing of Deep Neural Networks, has acquired MIPS Technologies for an undisclosed amount. Wave projects that the acquisition will be immediately cash-flow positive and accretive to its balance sheet and valuation. The deal logic is pretty sound, adding new markets such as edge AI computing while giving the company in-house RISC cores it can use for its next-generation DataFlow Processing Unit datacenter AI chip. Who is Wave Computing, and why does it need MIPS? Wave is an early innovator in AI silicon geared towards datacenter use, to train deep neural networks (DNNs) and run those networks for predictions and classifications.