FACT-Finder, a company that offers ecommerce companies tools to personalize their site with things like AI-driven recommendations, said it has acquired Loop54, a company that provides personalized search results. It's the latest in a trend of consolidation in the ecommerce world, where a host of companies arose to offer personalization with new technologies like AI, but now the bigger companies are gobbling up the smaller ones -- and specifically in the ecommerce software-as-a-service (SaaS) search market. On the smaller side, we reported last week on Coveo's acquisition of AI-powered personalization provider Qubit. On the much bigger side, yesterday, reports emerged that PayPal is making a $45 billion bid for e-commerce giant Pinterest. "With the expertise and unique approach that our new colleagues at Loop54 bring to the table, we will significantly expand our market leadership and push the bounds of what is possible in e-commerce," said Emile Bloemen, CEO of FACT-Finder.
Nearly 150,000 Tesla cars are using the company's new "safety score," a tool rolled out last month to determine whether owners can access the beta version of its "Full Self-Driving" software, executives said during its third quarter earnings call. While 150,000 cars are now part of the Full-Self Driving (FSD) beta enrollment program, a fraction of drivers have been given access to the software. Only 2,000 drivers have been able to test the FSD program over the past year. Earlier this month, Tesla rolled out version 10.2 to around 1,000 additional owners with perfect safety scores. Tesla charges $10,000 for the FSD software, which CEO Elon Musk has promised for years will one day deliver full autonomous driving capabilities.
Tesla's third-quarter profits more than quadrupled on sharply higher sales despite a global semiconductor shortage that has plagued the auto industry, according to results released Wednesday. Elon Musk's electric car company posted a record profit of $1.6 billion for the three-month period, as revenues surged 57 percent to $13.8 billion compared to the year-ago period. Tesla also delivered a record 241,391 vehicles during the period, with sales significantly ramping up in North America and China. The results suggest Tesla's output has been less affected by the global shortage of semiconductors than some rival carmakers that have shuttered factories or cut production. However, the company said chip shortages, as well as congestion at ports and rolling blackouts, "have been impacting our ability to keep factories running at full speed."
Tesla's third-quarter profits more than quadrupled on sharply higher sales despite a global semiconductor shortage that has plagued the auto industry, according to results released Wednesday. Elon Musk's electric car company posted a record profit of $1.6 billion for the three-month period, as revenues surged 57 percent to $13.8 billion compared to the year-ago period. Tesla also delivered a record 241,391 vehicles during the period, with sales significantly ramping up in North America and China. The results suggest Tesla's output has been less affected by the global shortage of semiconductors than some rival carmakers that have shuttered factories or cut production. However, the company said chip shortages, as well as congestion at ports and rolling blackouts, "have been impacting our ability to keep factories running at full speed." "We believe our supply chain, engineering and production teams have been dealing with these global challenges with ingenuity, agility and flexibility that is unparalleled in the automotive industry," Tesla said in its news release.
Gartner, Inc. announced its top 12 strategic technology trends for 2022 and beyond. Analysts presented their findings at the Gartner IT Symposium/Xpo 2021, heald virtually for the second year in a row, due to the pandemic. Gartner Research Vice President David Groombridge emphasized that just as 2020 and parts of 2021 found companies focused on survival, the future will focus on a return to the path toward growth. Just as survival required more creative use of technology, the path to growth will also emphasize creative use of technology, not so surprisingly. Gartner's strategic technology trends for 2022 and beyond are: Automation is a critical ingredient for digital transformation.
NoC interconnect IP to be dataflow backbone for image signal processors providing enhanced sensitivity, high-resolution HD imaging through low current, low power in a single-chip solution for the security/surveillance market. Eyenix's imaging solution provides a step-function advance over their previous product, replacing a 3rd-party artificial intelligence (AI) function with a superior capability developed in-house for super-resolution imaging. This is provided in a tightly integrated system design, including functions for image stabilization for mobile usage and image dewarping for wide-angle camera correction. The first application is destined for surveillance camera applications. Eyenix chose Arteris IP on-chip interconnect technology as a part of Eyenix's proprietary image processing chip because it enables Eyenix to design and integrate a complete and superior Eyenix imaging solution without dependency on external IP blocks for the AI function.
Edmonton, Alberta, Canada (September 20, 2021) – OneSoft Solutions Inc. (TSX-V:OSS; OTCQB:OSSIF) (the "Company" or "OneSoft") pleased to announce that a large U.S. pipeline operator (the "Client") has entered into a multi-year agreement with OneSoft's wholly owned subsidiary, OneBridge Solutions Inc. ("OneBridge") to integrate Cognitive Integrity ManagementTM ("CIM") software-as-a-service solution into its asset and integrity management practices for its pipeline operations. The Client is a midstream energy leader that transports approximately 30% of natural gas and crude oil in the U.S.A. and has operations in Canada and other countries. Company operations span numerous U.S. states and include facilities for natural gas midstream, intrastate and interstate transportation and storage; crude oil; natural gas liquids and fractionation; refined product transportation; terminal assets; and ownership stakes in other oil and gas operations. The Client currently operates approximately 90,000 miles of pipelines and is actively seeking acquisition of additional energy assets to continue its business growth. The agreement reflects a plan to initially onboard CIM for the Client's piggable pipelines over several years, which currently comprise approximately 45% of its infrastructure, with potential opportunity to subsequently incorporate probabilistic risk, direct assessment and other new CIM functionality enhancements for the majority of its pipeline assets in the future.
A massive disruption now appears imminent in one of the world's largest – and most important – industries. In much the same way that Amazon disrupted the retail business – and how PayPal disrupted the payments industry – one under-the-radar health technology company now seeks to transform the $11.85 trillion global health industry. By moving healthcare away from brick and mortar, traditional medicine into an AI-driven tool that offers unprecedented speed, efficiency, and accuracy... Investors still have a brief window of opportunity to get in on this transformational investment opportunity while it still flies beneath Wall Street's radar. But as you'll soon discover, this company's technology is so powerful that it could become a valuable addition to hundreds of millions of households worldwide. Whether most patients, providers, or large healthcare companies realize it or not, the healthcare industry is already in the early stages of significant change. That's because patients now desire access to more information – and better information – in the blink of an eye. In a recent survey of U.S. health consumers, 71% reported facing major frustrations through their experience with healthcare providers. Concerns ranged from difficulties scheduling appointments to impersonal visits.
Jeffrey Austin White has joined Holmes Murphy as its Chief Analytics Officer (CAO), bringing his nearly three decades of expertise focused on strategic investments in talent and technology to the national insurance brokerage. In this new role for Holmes Murphy, White will work to increase emphasis on innovation and data intelligence, helping to drive the company's potential and performance for clients. He will largely be responsible for defining and driving analytics and business intelligence initiatives, including assessing the current state of data and analytics capabilities, developing an analytics strategy, and leveraging innovations in artificial intelligence to propel Holmes Murphy and its clients forward. White will also be working to provide insight on potential opportunities for BrokerTech Ventures (BTV), the first broker-led convening platform and accelerator program focused on delivering innovation to the insurance broker industry. "Holmes Murphy continues to raise the bar when it comes to developing technology and innovations within the insurance industry. I'm excited to play a role in advancing their data analytics and AI capabilities," said White.
It's been a hot, hot year in the world of data, machine learning and AI. Just when you thought it couldn't grow any more explosively, the data/AI landscape just did: rapid pace of company creation, exciting new product and project launches, a deluge of VC financings, unicorn creation, IPOs, etc. It has also been a year of multiple threads and stories intertwining. One story has been the maturation of the ecosystem, with market leaders reaching large scale and ramping up their ambitions for global market domination, in particular through increasingly broad product offerings. Some of those companies, such as Snowflake, have been thriving in public markets (see our MAD Public Company Index), and a number of others (Databricks, Dataiku, Datarobot, etc.) have raised very large (or in the case of Databricks, gigantic) rounds at multi-billion valuations and are knocking on the IPO door (see our Emerging MAD company Index – both indexes will be updated soon). But at the other end of the spectrum, this year has also seen the rapid emergence of a whole new generation of data and ML startups. Whether they were founded a few years or a few months ago, many experienced a growth spurt in the last year or so. As we will discuss, part of it is due to a rabid VC funding environment and part of it, more fundamentally, is due to inflection points in the market. In the last year, there's been less headline-grabbing discussion of futuristic applications of AI (self-driving vehicle, etc.), and a bit less AI hype as a result. Regardless, data and ML/AI-driven application companies have continued to thrive, particularly those focused on enterprise use cases. Meanwhile, a lot of the action has been happening behind the scenes on the data and ML infrastructure side, with entire new categories (data observability, reverse ETL, metrics stores, etc.) appearing and/or drastically accelerating. To keep track of this evolution, this is our eighth annual landscape and "state of the union" of the data and AI ecosystem – co-authored this year with my FirstMark colleague John Wu. (For anyone interested, here are the prior versions: 2012, 2014, 2016, 2017, 2018, 2019 (Part I and Part II) and 2020.) For those who have remarked over the years how insanely busy the chart is, you'll love our new acronym – Machine learning, Artificial intelligence and Data (MAD) – this is now officially the MAD landscape! We've learned over the years that those posts are read by a broad group of people, so we have tried to provide a little bit for everyone – a macro view that will hopefully be interesting and approachable to most; and then a slightly more granular overview of trends in data infrastructure and ML/AI for people with deeper familiarity with the industry. This (long!) post is organized as follows: Let's start with the high level view of the market. As the number of companies in the space keeps increasing every year, the inevitable questions are: why is this happening?