Venture capital (VC) funding slid more deeply in AI & ML than in software overall in Q2, "falling 27.8% quarter-over-quarter (QoQ) compared to 21.6% for IT more generally." Both deal value and deal count "fell to their lowest levels since Q4 2020, also lagging the rest of IT," the report from Pitchbook revealed. Of the 70 product categories the firm tracks, "only 21 are on pace to grow in VC funding in 2022, driven by leading vertical applications including sales & marketing, information security, and drug discovery." The update from Pitchbook also mentioned that horizontal platform investment "is lagging, as outsized revenue projections face market realities, with AI-as-a service (AIaaS) investment on pace to decrease 87.7% in 2022." Numerous AI platform companies "have struggled to reach revenue forecasts in the current financial environment, creating a greater emphasis on vertical applications that can rapidly deliver value."

The $213m venture financing of Astronomer was the technology industry's top artificial intelligence venture financing deal as total deals worth $5bn were announced globally in March 2022, according to GlobalData's deals database. The value marked an increase of 35.05% over the previous month of $3.68bn and a drop of 12.8% when compared with the last 12-month average, which stood at $5.7bn. Comparing artificial intelligence venture financing deals value in different regions of the globe, North America held the top position, with total announced deals in the period worth $2.69bn. At the country level, the US topped the list in terms of deal value at $2.59bn. In terms of volumes, North America emerged as the top region for technology industry artificial intelligence venture financing deals globally, followed by Asia-Pacific and then Europe.

From the beginning of the 2010s, big data and AI have been trending up to unleash revolutionary changes in many industries. Universities have set up data science programs and investors are pouring tons of dollars into AI-related startups. The US and China have long been the focus of AI development as these two countries have the most AI unicorns and investment activities. Among the top 20 most valuable AI unicorns, the US takes 9 and China takes 7 while the UK and Japan take 3 and 1 respectively. While the US and China outshine the rest in a global scale, the UK is the supernova in Europe, acting as the womb of the most regional AI startups.

VC funding and M&A deal activity in the AI space remained inconsistent in both value and volume terms during Q1 2019 – Q4 2019. However, despite the fluctuations, both VC and M&A deal volume showcased an increase in Q4 2019 compared to Q4 2018. In contrast, VC and M&A deal value declined in Q4 2019 compared to Q4 2018. Aurojyoti Bose, Lead Analyst at GlobalData, comments: "AI start-ups have been getting lots of VC investors' attention for the past few years. However, the growth in deal value has slowed recently, which seems to be a short-term phenomenon with long-term prospects likely to remain positive."

From the beginning of the 2010s, big data and AI have been trending up to unleash revolutionary changes in many industries. Universities have set up data science programs and investors are pouring tons of dollars into AI-related startups. The US and China have long been the focus of AI development as these two countries have the most AI unicorns and investment activities. Among the top 20 most valuable AI unicorns, the US takes 9 and China takes 7 while the UK and Japan take 3 and 1 respectively. While the US and China outshine the rest in a global scale, the UK is the supernova in Europe, acting as the womb of the most regional AI startups.

Essentially, it's a web app that guides admins through building machine learning models with a few clicks and without having to write any code. As I mentioned, it allows them to make any different objects. We have this machine learning pipeline, an automated machine learning pipeline, in the back end, that trains all the models once we receive the info on the front end. We need to serve many different use cases and we don't have an intimate look ourselves at the data; just some of the example use cases of use, some common ones, binary classification. A lot of customers have subscription-based models, and they might have records of all the customers who have left in the past year or so.

A flurry of technology mergers and acquisitions (M&A) are set to happen before 2020, a new report predicts. However private equity firms – which have recently been elbowing trade buyers out of the way to splash the cash on tech targets, such as in the $5.3bn (£3.8bn) buyout of Nets – could soon see their bubble burst. According to a report from tech-focused deal advisers Hampleton Partners, the availability of cheap debt has allowed private equity to outbid trade buyers. But as interest rates look set to rise, this bubble could burst – possibly causing a price correction. "Despite the slowdown in the second half of last year, the overall outlook in the foreseeable future is very positive as continued technological disruption forces established vendors and new market entrants to innovate and stay competitive via tech M&A," said Hampleton founder Miro Parizek.

The relentless drive to digital transformation among tech and non-tech companies pushed mergers and acquisitions to record levels over the past year, the latest analysis finds. Now, artificial intelligence and machine learning loom as the next wave of hot targets for companies seeking new market leverage. EY, which tracks M&A activity quarter-by-quarter and year-by-year, puts aggregate 2016 deal value at $466.6 billion, exceeding 2015 levels by two percent -- and establishing the highest level ever recorded. However, the actual volume of M&A deals has colled somewhat, to 3,076 deals, a five-percent decline. At the core of this deal-making frenzy is interest in the Internet of Things (IoT), in which deal value tripled to $103.4 billion through 2016.

The relentless drive to digital transformation among tech and non-tech companies pushed mergers and acquisitions to record levels over the past year, the latest analysis finds. Now, artificial intelligence and machine learning loom as the next wave of hot targets for companies seeking new market leverage. EY, which tracks M&A activity quarter-by-quarter and year-by-year, puts aggregate 2016 deal value at $466.6 billion, exceeding 2015 levels by two percent -- and establishing the highest level ever recorded. However, the actual volume of M&A deals has colled somewhat, to 3,076 deals, a five-percent decline. At the core of this deal-making frenzy is interest in the Internet of Things (IoT), in which deal value tripled to $103.4 billion through 2016.