Throughout 2020, venture capital firms continued expanding into new global markets, with London, New York, Tel Aviv, Toronto, Boston, Seattle and Singapore startups receiving increased funding. Out of the 79 most popular A.I. & ML startup locations, 15 are in the San Francisco Bay Area, making that region home to 19% of startups who received funding in the last year. Israel's Tel Aviv region has 37 startups who received venture funding over the last year, including those launched in Herzliya, a region of the city known for its robust startup and entrepreneurial culture. Please see the Roundup Of Machine Learning Forecasts And Market Estimates, 2020 for additional market research on A.I. and machine learning. The following graphic compares the top 10 most popular locations for A.I. & ML startups globally based on Crunchbase data as of today: Augury – Augury combines real-time monitoring data from production machinery with AI and machine learning algorithms to determine machine health, asset performance management (APM) and predictive maintenance (PdM) to provide manufacturing companies with new insights into their operations.
Datanomix, a production intelligent software vendor, today announced it has raised $6 million in series A funding to expand the reach of its software. Co-led by Gutbrain Ventures and PBJ Capital, the company says it will put the funds toward growing its sales, marketing, customer success, and engineering departments. Manufacturing is undergoing a resurgence as business owners look to modernize their factories and speed up operations. According to ABI Research, more than 4 million commercial robots will be installed in over 50,000 warehouses around the world by 2025, up from under 4,000 warehouses as of 2018. In China, Oxford Economics anticipates 12.5 million manufacturing jobs being automated, while in the U.S., McKinsey projects machines will take upwards of 30% of such jobs.
Coming off its best quarter ever, SoftBank is on the hunt for its next billion dollar IPO. Having funded 29 of the 657 unicorns in the world, according to CB Insights, the Japanese telecom giant has been on a shopping spree, looking for promising new AI startups to bet big on. At Collision's tech conference held online last month, I had a chance to talk with the CEOs of SoftBank's newest portfolio companies, Standard Cognition and Forward. Here's how the two San Francisco startups are leveraging artificial intelligence to help gain market dominance in the post-pandemic world. In 2017, a group of machine learning engineers at the SEC became obsessed with computers that could see better than humans and ditched their jobs to join Y Combinator to build the computer vision company of their dreams.
OpenSpace, a platform that helps construction companies track building projects through AI-powered analytics and 360-degree photo documentation, has raised $55 million in a series C round of funding led by Alkeon Capital Management. The raise comes amid a cross-industry digital transformation boom, spurred in large part by the pandemic. Construction has often lagged behind other sectors in terms of efficiency, but technology such as robotics, artificial intelligence (AI), and remote collaboration tools have played a sizable role in getting the $11 trillion industry back on track. Founded out of San Francisco in 2017, OpenSpace leans on AI to create 360-degree photos of construction sites, which are captured by builders or site managers who traverse an area with cameras strapped to their hats. All the imagery is sent to the cloud, where computer vision and machine intelligence tools arrange, stitch, and map the capture visuals to the associated project plans.
Robotic process automation has become buzzy in the last few months. New York-based UiPath is on course to launch an initial public offering after gaining an astounding valuation of $35 billion in February. Over in China, homegrown RPA startup Laiye is making waves as well. Laiye, which develops software to mimic mundane workplace tasks like keyboard strokes and mouse clicks, announced it has raised $50 million in a Series C round. The proceeds came about a year after the Beijing-based company pulled in the first tranche of its Series C round.
A staggering amount of money is pouring into data center AI chip companies at the moment. Data center AI chip companies are raising eye-watering amounts of money. In the last week, we've seen Groq announce a $300 million Series C round of funding, and SambaNova raise a staggering $676 million Series D. SambaNova is now valued at somewhere above $5 billion. They are not the only ones in this sector raising these huge amounts of money. Fellow data center AI chip companies Graphcore (raised $710 million, valued at $2.77 billion) and Cerebras (raised more than $475 million, valued at $2.4 billion) are hot on their heels as the sector continues to gain momentum.
By number of investments, US-based companies outnumbered the top ten VC (venture capital) investors in the artificial intelligence (AI) space in 2020. According to GlobalData, a leading data and analytics company, Sequoia Capital topped the list, having participated in 52 VC funding rounds. Sequoia Capital is a technology-focused venture capital company based in the United States. It invests in both public and private firms. The company focuses in private company incubation, seed stage, startup stage, early stage, and growth stage investments.
As a company founded by data scientists, Streamlit may be in a unique position to develop tooling to help companies build machine learning applications. For starters, it developed an open-source project, but today the startup announced an expanded beta of a new commercial offering and $35 million in Series B funding. Sequoia led the investment with help from previous investors Gradient Ventures and GGV Capital. Today's round brings the total raised to $62 million, according to the company. Data scientists can download the open-source project and build a machine learning application, but it requires a certain level of technical aptitude to make all the parts work.
Enterprise analytics company Clarify Health has secured $115 million in series C funding to scale its self-service healthcare analytics cloud and business software. Clarify Health combines longitudinal data for more than 300 million "unique patient lives" from government and commercial claims, electronic health records (EHRs) and prescriptions, according to the company. These data can help healthcare professionals manage population health and commercialize pharmaceutical and biotechnology products. "By linking CMS claims data with commercial claims, EHR, prescription and socioeconomic data, our models are trained on large cohorts and a more complete picture of each patient's longitudinal healthcare journey," Clarify Health CEO Jean Drouin, M.D., told Fierce Healthcare. The San Francisco-based company was launched in 2015 and has raised $178 million to date, according to Crunchbase.
Welcome back to The TechCrunch Exchange, a weekly startups-and-markets newsletter. It's broadly based on the daily column that appears on Extra Crunch, but free, and made for your weekend reading. If you want it in your inbox every Saturday morning, sign up here. Let's talk money, startups and spicy IPO rumors. This week, Scale AI raised a $325 million Series E. The company, as TechCrunch has written, works in the data labeling space. And it has been on a fundraising tear over the last few years.