A collateral beneficiary of the feverish pace of generative artificial intelligence development appears to be the humanoid robot. A Norwegian company called 1X Technologies, formerly Halodi Robotics, which describes itself as a manufacturer and inventor of androids, recently attracted $23.5 million in a round of funding led by the OpenAI Startup Fund -- the same OpenAI that got the AI snowball rolling with its ChatGPT generative AI bot. "1X is at the forefront of augmenting labor through the use of safe, advanced technologies in robotics," Brad Lightcap, OpenAI's COO and manager of the OpenAI Startup Fund, said in a statement. "The OpenAI Startup Fund believes in the approach and impact that 1X can have on the future of work." With the funds, 1X said it intends to accelerate the development of its bipedal android model NEO and expand manufacturing of its first commercially available wheel-based android, EVE, in Norway and North America.

"Unfortunately, there's no way to quantify the size of this problem," said Brandon Purcell, a Forrester vice president, principal analyst, and co-author of the report, adding "… it's true that we are far from artificial general intelligence, but AI is being used to make critical decisions about people at scale today--from credit decisioning, to medical diagnoses, to criminal sentencing. These could include business leaders, lawyers, security and risk specialists, as well as activists, nonprofits, members of the community and consumers. Accounting for intersectionality or how different elements of a person's identity combine to compound the impacts of bias or privilege. "The key is in adopting best practices across the AI lifecycle from the very conception of the use case, through data understanding, modeling, evaluation, and into deployment and monitoring," Purcell said. "Unfortunately, there's no way to quantify the size of this problem," said Brandon Purcell, a Forrester vice president, principal analyst, and co-author of the report, adding "… it's true that we are far from artificial general intelligence, but AI is being used to make critical decisions about people at scale today--from credit decisioning, to medical diagnoses, to criminal sentencing.

Merger and acquisition activity among analytics vendors has picked up in recent months. After more than a year between Salesforce's $15.7 billion acquisition of Tableau in June 2010 and Tibco's purchase of IBI (formerly Information Builders) for an undisclosed amount in October 2020, recent months have been a busy time for merger and acquisition activity. Talend was acquired by private equity firm Thoma Bravo in March 2021. Logi Analytics was acquired by ERP vendor Insightsoftware in April 2021 and subsequently purchased Izenda just eight days later. And ThoughtSpot, after going nine years without acquiring another company, has acquired two so far in 2021.

With AI use continuing to grow in adoption throughout enterprise IT, Deloitte is creating a new Deloitte Center for AI Computing to advise its customers, explain the technology and help them use it in their ongoing business and growth plans. Designed to provide a cloud-accessible accelerated platform that Deloitte clients can use to test and explore various AI strategies and tools, the infrastructure features six Nvidia DGX A100 systems, Nvidia Mellanox networking, high-performance storage and Nvidia software. The platform will be physically hosted in Deloitte's datacenter in Hermitage, Tenn., but will also be part of a virtual service. Based on Nvidia's DGX POD reference architecture and harnessing the power of 48 A100 GPUs, the installation will serve as an AI acceleration engine for Deloitte's clients, the company said. The new facility was announced on Tuesday (March 2).

With AI use continuing to grow in adoption throughout enterprise IT, Deloitte is creating a new Deloitte Center for AI Computing to advise its customers, explain the technology and help them use it in their ongoing business and growth plans. Designed to provide a cloud-accessible accelerated platform that Deloitte clients can use to test and explore various AI strategies and tools, the infrastructure for the virtual center will be physically hosted in Deloitte's data center in Hermitage, Tenn., featuring an Nvidia DGX POD with six Nvidia DGX A100 systems as its core. The Deloitte Center for AI Computing will also be equipped with Nvidia Mellanox networking and high-performance storage to help clients create with AI, according to the company. The new facility was announced on Tuesday (March 2). "The Nvidia systems are being deployed this month and the center will be available to clients starting later in March," Nitin Mittal, the AI strategic growth offering leader for Deloitte Consulting, told EnterpriseAI.

Over the past few years, we have seen the IoT and its boundless potential take off. With a pandemic fueled 2020, digital transformation accelerated rapidly, and with increased connectivity, thanks to 5G and faster WiFi and improvements in AI and machine learning, IoT looks set to deepen its roots in our lives and industries. As we close out 2020 and look ahead to 2021 and beyond, we see not just growth in the IoT, but increased use cases and trends surrounding them. The following is a deeper look at the biggest trends taking shape in the next year. If there's one thing the success of Alexa, Ring, Nest, and other smart home devices have taught us, it's that the IoT is nearly everywhere, if it's not already.

There's one thing that none of us saw coming this year -- rapid digital transformation that saw years of innovation in about 5-6 months (and in some cases less). We saw companies shifting and technologies getting adopted almost overnight, and I don't think it's going to stop, especially in some areas like AI, which was already seeing rapid acceleration. Those of us working in the tech field see a solid expansion and development of the use of AI in really cool, important, and meaningful ways in 2021 and beyond. While the past few years have allowed many companies to dip their toe into AI, ML, intelligent automation, and other similar solutions, 2020 proved to be the year to dive in headfirst. The proliferation of AI is happening at a great pace both at the chip level and the software level, and make no mistake; the two things are deeply intertwined.

Apple has long been the lone wolf of the personal computer industry in maintaining its own operating system instead of licensing Microsoft's Windows as rivals do. Tuesday it struck out further from the pack by launching its first laptops and desktops built on processors designed wholly in house. The silicon shift gives Apple new control over its own destiny--and perhaps the future of the personal computer. The change was long expected. Tuesday the company unveiled the first Macs built on a processor, the M1, designed by Apple's own chip engineers, abandoning the industry's dominant supplier, Intel.

When it comes to technologies that got a big boost from the response to the pandemic, probably the first thing that comes to mind is video conferencing, followed closely by other collaboration tools. Zoom announced August 31 that its revenue for the second quarter was up 355% year over year. Maybe that's why everyone is talking about Zoom fatigue. But video conferencing isn't the only technology that's gotten a boost as companies try to navigate the challenges of a pandemic. Chatbot use and deployment is also on the rise.

Machine learning has moved from the stuff of science fiction to a staple of modern business, as organizations across nearly every industry vertical implement ML technologies. Doctors are using machine learning to more accurately diagnosis and treat their patients, retailers are using ML to get the right merchandise to the right stores at the right time, and researchers are utilizing the technology to develop effective new medicines. That is just a sliver of the use cases emerging, as all sectors -- from energy and utilities, to travel and hospitality, to manufacturing to logistics -- and the various functions within any given organization increasingly put machine learning to work. Machine learning is a subset of artificial intelligence, where computers use algorithms to learn from data, allowing the machines to identify patterns -- a capability that organizations can put to use in multiple ways. Experts said machine learning enables organizations to perform tasks on a scale and scope previously impossible to achieve.