Long thought of as a tool to increase efficiency and save costs, AI has now proven to be an innovation driver that enables business growth. According to our latest Accenture research on AI among 1,200 global companies, "AI Achievers"--those companies that are the most AI-mature--enjoy 50% greater revenue growth, clearly outpacing their competitors. Why, then, are most organizations (63%) stuck in the experimentation phase with AI? Because AI initiatives are often led with timidity and are hampered by "pilot-itis," a fixation on pilot projects at the expense of scale. Speaking to a select group of CEOs as part of the research revealed an opportunity--and the need--for companies' most senior leaders to increase their AI expertise.

Square Off charmed us at CES 2019, when the startup showed off its robotic chess board at our Hardware Battlefield event. Watching the pieces move on their own, courtesy of underlying AI, grabbed the attention of a jaded crowd of showgoers. This morning, it takes the next step in the startup lifecycle, as Bay Area-based kids robotics firm Miko announces that it has acquired a majority stake of 70% of the firm. "We're thrilled to join forces with Miko on this journey to revolutionize edutainment for kids," Square Off's co-founder and CEO, Bhavya Gohil, says in a short press release tied to the news. Miko, meanwhile, is a Disney Accelerator grad best known for its eponymous toy robot.

The onshoring and buildout of dozens of fabs, many costing tens of billions of dollars, is beginning to spill over into other areas that are critical for chip manufacturing. Materials, in particular, which often gets little attention outside of chip manufacturing, witnessed a big spike in September 2022. In fact, seven materials companies covered in this report made up more than a third of the month's total reported investments, with three of the companies garnering more than $200 million. Other investment targets were sputtering equipment and evaporation materials for deposition, high-purity polycrystalline silicon, fluorine-containing electronic gases, and silicon carbide. In the AI hardware arena, numerous startups are focusing on in-memory and near-memory compute, reducing the volume of data that needs to be moved back and forth between memory and processing elements. Novel architectures also are appearing, such as one that uses sparse mathematics.

In this article, we will discuss the 10 best machine learning stocks to invest in. If you want to explore similar stocks, you can also take a look at 5 Best Machine Learning Stocks To Invest In. According to an industry analysis report by Fortune Business Insights, the global machine learning industry was valued at $15.4 billion in 2021 and is expected to reach a value of over $21 billion in 2022. The machine learning industry is expected to grow at a compound annual growth rate of 38.8% from 2022 through 2029 and reach a value of $210 billion by the end of 2029. One of the major drivers of this growth is the increasing adoption of machine learning in a variety of industries including technology, healthcare, manufacturing, automotive, retail, advertising, automation, defense, and financial services among others.

Investors looking for the best robotics stocks to buy have a lot of things to consider. In response to the global pandemic, supply-chain bottlenecks, trade issues, and geopolitical tensions, most U.S.-based businesses are looking to relocate production closer to their domestic facilities. The nearshoring trend is already taking off, and robotics is expected to be a critical piece of the puzzle. Hence, robotics stocks should take off in a big way in the future. Swiss Tech Leader ABB recently revealed the results of a survey showing how more than 60% of the U.S. and European respondents are exploring reshoring and nearshoring operations to build resilience amidst global challenges.

It's no secret that agile companies, those that can quickly respond and pivot when necessary, fare better than those that falter when faced with uncertainty or change. A recent IDC global report shows that agile companies experience higher profits, revenue growth and impressive market share gains. They also have stronger employee retention rates, faster time to market and better customer experiences. Yet, being able to adapt to change and successfully deal with the unexpected requires a steadfast focus on the future, and many organizations today are too bogged down with the here-and-now to focus on what lies ahead. As company leaders increasingly search for ways to achieve agility and future-proof their businesses, automation technology is becoming a key initiative.

Investment professionals rely on extrapolating company revenue into the future (i.e. revenue forecast) to approximate the valuation of scaleups (private companies in a high-growth stage) and inform their investment decision. This task is manual and empirical, leaving the forecast quality heavily dependent on the investment professionals' experiences and insights. Furthermore, financial data on scaleups is typically proprietary, costly and scarce, ruling out the wide adoption of data-driven approaches. To this end, we propose a simulation-informed revenue extrapolation (SiRE) algorithm that generates fine-grained long-term revenue predictions on small datasets and short time-series. SiRE models the revenue dynamics as a linear dynamical system (LDS), which is solved using the EM algorithm. The main innovation lies in how the noisy revenue measurements are obtained during training and inferencing. SiRE works for scaleups that operate in various sectors and provides confidence estimates. The quantitative experiments on two practical tasks show that SiRE significantly surpasses the baseline methods by a large margin. We also observe high performance when SiRE extrapolates long-term predictions from short time-series. The performance-efficiency balance and result explainability of SiRE are also validated empirically. Evaluated from the perspective of investment professionals, SiRE can precisely locate the scaleups that have a great potential return in 2 to 5 years. Furthermore, our qualitative inspection illustrates some advantageous attributes of the SiRE revenue forecasts.

IBM announced plans to acquire Dialexa, a leading U.S. digital product engineering services firm, to help companies drive innovation and achieve their digital growth agendas. The acquisition is expected to deepen IBM's product engineering expertise and provide end-to-end digital transformation services for clients. Dialexa will be the sixth acquisition IBM has made in 2022, further bolstering the company's hybrid cloud and AI skills and capabilities. Since Arvind Krishna became CEO in April 2020, IBM has acquired more than 25 companies. Thirteen of those acquisitions, including Dialexa, have been in IBM Consulting.

A startup backed by a billionaire Brazilian family is partnering with e-commerce platform Farmers Business Network to offer robots that spray fertilizer and pesticides to US farmers. Solinftec's robots, which run on solar panels, are autonomous and were designed to apply fertilizer and weed killer only where needed. The company said the technology, already in use in Brazil, can reduce product use by as much as 70%. As a result of the deal, both companies will work with farmers in the US to commercialize the robot and to develop new methods for agrochemicals to be used with robotics technology.

Seattle-based venture capital firm Madrona Venture Group announced today it has raised a bumper $690 million for two oversubscribed funds that will be used to back promising technology startups in the Pacific Northwest region, Silicon Valley and beyond. The $430 million Madrona Fund 9 and the $260 million Acceleration Fund 3 saw 100% of existing institutional investors participate, Madrona said. Combined, they represent an almost 40% increase over the funds Madrona raised in 2020. The funds will be used to invest in technology firms ranging from pre-seed all the way through to Series C startups. Madrona is one of the more prominent of tech-focused venture capital firms, focusing on seed, early-stage and acceleration-stage startups that leverage technology and promise to disrupt huge existing markets.