Set up by an ex-Google employee, Reflektion's customer data and insights enable businesses to influence customers at every relevant point of engagement. It may be the time of mobile phones and apps, but business websites are often the primary point for prospective customers to gather information. There are ad-tech companies that track why people visit a particular website and target them with relevant advertising. However, this form of technology is relevant to a media or publishing company. What about businesses keen to understand the profile of traffic coming to their website and convert them to prospective leads?
Artificial intelligence (AI) is set to substantially disrupt the financial services industry, transforming how we bank, invest, and get insured. AI refers to machines that are capable of performing specific tasks that normally require human intelligence such as visual perception, speech recognition, decision-making, and language translation. AI and related technologies are made possible by the colossal volumes of data we are able to collect and process. AI has been all the buzz these past few years, and according to CB Insights, AI startups raised over US$2 billion in 2016 alone. In the area of financial services, AI is expected to bring major shifts in financial institutions' workforces.
As an extension to its Data Lake Management Platform, Zaloni has introduced a machine-learning data matching engine, which leverages the data lake to create "golden" records and enable enriched data views for multiple use cases across business sectors. Zaloni's data matching engine provides a new approach for creating an integrated, consistent view of data that is updated, efficiently maintained and can drive customer-facing applications. It addresses a gap in the marketplace for a simplified, much less expensive and faster-to-implement solution for data mastering. Many master data records solutions are complex, inflexible, expensive and underperform for the cost," said Ben Sharma, Zaloni's CEO. "Zaloni's data matching engine, which is offered as an extension to Zaloni's Data Lake Management Platform, enables a practical, unique solution at a great value that will interest any organization that has a Customer or Product 360 initiative.
Infosys, a global leader in technology services and consulting, is aiming to reinvent the way people consume sport using extensive player data. The Indian firm, which had revenues of $9.5 billion in its last financial year, demonstrated its'Infosys Information Platform (IIP)' during the recent ATP Tennis tournament in London, of which it was a headline sponsor. Speaking to Access AI, the firm's head of energy and services for Europe Mohamed Anis, who joined in 2000, said Infosys uses machine learning to analyse historical data on player performance, which in turn is able to predict behaviour, shot selection, and even a probabilistic outcome of the match itself. Anis (pictured) said the data is delivered in real time and can be used to help spectators view the game/match on an entirely different level – comparable to that of the coach. "Tennis has been around for a very long time," explained Anis.
The invention of artificial things that learn and perform actions took place in the classic times. Alongside Calculus Ratiocinator by Llull, there were many fictional stories and dramas depicting artificial things and their immense potentials. You must watch it if you haven't. Church-Turing thesis -- which means machines can simulate any process of formal reasoning (from Wiki). Theory that backed up the brains of creators like Allen Newell, Herbert Simon, John McCarthy, Marvin Minsky, and Arthur Samuel.
Intel and Amazon are partnering to combine the former's silicon and smarts with the latter's Alexa voice platform. The chipmaker has introduced the Intel Speech Enabling Developer Kit to provide a "complete audio front-end solution for far-field voice control," according to a press release. The idea is that Intel has done the hard work of designing the mic arrays and voice systems and that all developers will need to do is write applications for them. It offers algorithms for echo cancellation and beam forming, wake words, an 8-mic array and the company's dual digital signal processor. The development kit is up for pre-order starting today for $399.
At first blush, Scot Barton might not seem like an AI pioneer. He isn't building self-driving cars or teaching computers to thrash humans at computer games. But within his role at Farmers Insurance, he is blazing a trail for the technology. Barton leads a team that analyzes data to answer questions about customer behavior and the design of different policies. His group is now using all sorts of cutting-edge machine-learning techniques, from deep neural networks to decision trees.
Pure Storage (NYSE: PSTG), a leading independent all-flash data platform vendor for the cloud era, announced significant customer momentum for FlashBlade, the system purpose-built for modern analytics. Since general availability in January 2017, FlashBlade has gained traction among organizations running and innovating with emerging workloads, specifically modern analytics, artificial intelligence (AI) and machine learning (ML). Data is at the center of the modern analytics revolution. Large amounts of data must be delivered to the parallel processors, like multi-core CPUs and GPUs, at incredibly high speeds in order to train machine learning and analytic algorithms faster and more accurately. Today, most machine learning production is undertaken by hyperscalers and large, web-scale companies.
For decades we've been told robots were to blame for the dearth of manufacturing jobs in the US, but that's about to change. Veo Robotics has a counter-intuitive vision for the future: If you improve the robots, manufacturers will be able to hire more people for better jobs. I am proud to share that Lux Capital is partnering with Patrick, Clara and Scott to help them achieve their mission to create more collaborative industrial robots. We, along with our partners at GV, are leading a $12 million Series A venture investment in Veo Robotics. As part of the investment, I will be joining the board of directors.
About a year ago, Adobe announced its Sensei AI platform. Unlike other companies, Adobe says that it has no interest in building a general artificial intelligence platform -- instead, it wants to build a platform squarely focused on helping its customers be more creative. This week, at its Max conference, Adobe provided both more insight into what this means and showed off a number of prototypes for how it plans to integrate Sensei into its flagship tools. "We are not building a general purpose AI platform like some others in the industry are -- and it's great that they are building it," Adobe CTO Abhay Parasnis noted in a press conference after today's keynote. "We have a very deep understanding of how creative professionals work in imagining, in photography, in video, in design and illustration.