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Why some AI companies are securing massive funding despite economic downturn

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Tech startups are going through tough times as a result of a slowdown in growth capital. Investment firms are advising their portfolio companies to extend their runway. Companies are suffering from valuation markdowns and resorting to layoffs to cut costs. 

The artificial intelligence (AI) market is no exception. The CB Insights State of AI report for Q2 2022 shows global funding for AI startups dropped for the third consecutive quarter with a 21% decrease quarter-over-quarter. Mega-round fundings (i.e., rounds of more than $100 million) have seen a 33% drop quarter-over-quarter and only 12 new AI unicorns were born, the lowest since Q4 2020.

At the same time, the market has seen a 116% increase in exits – 90% of which are mergers and acquisitions, indicating that startups are gravitating toward large and financially stable companies as they continue to face cash problems.

However, amid the economic downturn, some AI startups have had no trouble raising huge investment rounds. And they hint at where the AI market might be headed in the near future.

Research labs led by AI celebrities are hot

Among the recipients of top equity deals in 2022 are AI research labs Anthropic ($580 million in series B) and Inflection AI ($225 in venture capital).  

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Anthropic’s website describes the lab as “an AI safety and research company that’s working to build reliable, interpretable and steerable AI systems.” It further says that it aims to address the unpredictability, unreliability and opacity of current AI systems. The company acknowledges that it’s currently focused on research with foreseeable opportunities to “create value commercially and for public benefit.” Since its founding in 2021, the company has released several research papers on transformer neural networks, large language models (LLMs) and reinforcement learning. 

That, by itself, doesn’t sound like a convincing pitch to make during an economic downturn. But perhaps what makes Anthropic interesting is that it was cofounded by Dario Amodei, the former VP of research at OpenAI.

After the $580 million fundraise in April, Amodei declared that the company will “explore the predictable scaling properties of machine learning systems, while closely examining the unpredictable ways in which capabilities and safety issues can emerge at scale.”

Research on safety and interpretability are crucial to the application of AI in the real world. But it’s also expensive, especially when it is applied “at scale” as Anthropic aims to do. Large-scale machine learning models are expensive to train and run, which suggests that Anthropic will soon need to raise more capital or find a large tech company that can monetize its technology. 

Inflection AI, the other research lab that has secured a megadeal, presents itself as “an AI-first company, redefining human-computer interaction.” Inflection aims to leverage recent advances in AI to develop the “ability to relay our thoughts and ideas to computers using the same natural, conversational language we use to communicate with people.”

This suggests that the company will be focused on LLMs, an exciting and costly area of research that still has many challenges to solve. The company was cofounded by Mustafa Suleyman, cofounder of DeepMind, and Reid Hoffman, cofounder of LinkedIn. The company has also recently recruited AI scientists from Google and Meta, according to CNBC.

Inflection launched in March with $225 million in funding from Greylock Partners, a VC firm that counts Suleyman and Hoffman as its partners. Given the costs of research and talent the company is facing, this probably won’t be the last we hear of it securing megadeals.

Healthcare, fintech and retail AI startups still raising funding

There is no shortage of ideas to apply AI to real-world applications. But during the downturn, areas of applied AI with more promising results continued to raise funding while others stagnated.

According to the CB Insights report, retail tech AI funding increased 24% in Q2 2022, nearing its pre-downturn levels. The biggest winner was Faire, which raised two rounds of extension to its series G funding, totaling $596 million. 

Faire is a marketplace that connects indie brands with local retailers that can sell their goods. It uses machine learning at different levels of its platform, including matching the supply-and-demand side of the market, helping brands better present their catalogs and profiles, optimizing search and recommendations for retailers and managing risk.  

Funding in healthcare AI decreased by 20% in Q2 2022 but is still doing much better than many other sectors. The biggest deal went to Biofourmis, which raised $300 million in series D. Biofourmis uses machine learning to monitor patients and predict diseases. The company uses hardware sensors paired with FDA-approved software that continually analyzes biomarkers, like heart rate, temperature and respiration rate. Predictive models have much potential to improve patient health and reduce the costs of care.

Fintech AI has managed to maintain its funding levels. The biggest deal went to Germany-based Taxfix, which nabbed $220 million in series D. Taxfix is a mobile assistant for tax returns. Users give the app a snapshot of their payslip and fill out a few additional details. The app provides them with their tax situation and estimated refund. For a premium, the app will also file taxes on the user’s behalf. The company uses machine learning and rule-based AI to automate the process of filling out tax forms and filing taxes. With its growing user base, the company, valued at $1 billion after the new round of funding, will now focus on expanding to new markets and creating new products to extend its touch points with customers beyond tax season.

Tricky times for AI startups

As capital becomes scarce, AI startups that are venturing into uncharted lands will find it harder to get funding. AI luminaries seem to be the exception to the rule, and they will continue to attract investors who have room to wait for long-term returns on investments.

AI companies that have already established their product/market fit and have a solid user base will also have a greater chance of raising funding during the downturn, as investors will be looking for startups that are ready for aggressive growth and, given enough capital, can shortcut their path to profitability.

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AI

Posh Technologies fuels call center automation with $27.5M funding

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As call volumes skyrocketed during the pandemic, contact centers turned to AI to help distribute the workload. But even before the pandemic, customer service departments were experimenting with automation solutions, including chatbots and transcribers, to streamline operations. A 2019 Deloitte survey found that 76% of contact centers were planning to invest in AI in the next two years. According to that same survey, 57% of companies were testing the use of AI in assisting customer service agents. 

Anticipating the trend, Karan Kashyap founded Posh Technologies, a Boston, Massachusetts-based conversational AI and natural language processing technology development company, in 2018. Today, Posh announced that it raised $27.5 million in series A funding led by Canapi Ventures. Kashyap, who serves as CEO, says that the proceeds will be put toward supporting additional investment in product research and development and the expansion of Posh’s platform.

“Posh’s growth accelerated during the pandemic amid the increasingly digital world which we continue to live in. Just as the pandemic started, we were already getting ready to hit the gas pedal. The pain points and needs of financial institutions changed from the pandemic to our benefit, including needing to better manage customer service on a 24/7 basis, managing increased call volumes from closed branches, and doubling down on self service solutions,” Kashyap told VentureBeat via email. “There was also high turnover for those customer service jobs — the ‘great resignation’ took a toll on call center jobs too. While Posh’s aim is not to replace human agents, our technology helps our customers address higher volumes and augment their current service models.”

Augmenting customer service

Kashyap, who has a bachelor’s degree in computer science and a master’s in AI, developed Posh’s technology while studying at MIT. The platform provides chatbots that automate customer questions and workflows on the web, SMS, and messaging apps for tasks like checking hours and making payments. A separate IVR bot replaces traditional dialpad menus with natural, voice-driven conversations with customers.

On the backend, Posh automates contact center and help desk FAQs and workflows, leveraging machine learning and natural language processing to give chatbots “memory persistence.” Concretely, Posh’s systems train on domain-specific data so that its chatbots understand some of the nuances of a given industry’s — and company’s — language.

Posh integrates with live chats as well as other “API-friendly systems” (e.g., digital banking databases and telephony) and escalates to human reps if need be. Customers get metrics showing how conversations went and where areas for improvement might exist.

“Our AI can easily manage routine inquiries without requiring staff involvement. We see it as the first line of defense to get people out of queues while also enabling round-the-clock self service,” Kashyap said. “Credit unions and banks are often able to answer customers’ questions directly on their website through the Posh chatbot feature. In cases where the chatbot doesn’t have the right answer, it can intelligently escalate the request to a call center or in-person representative, significantly improving both the amount of money spent on customer service as well as the customer experience.”

Competition

Beyond incumbents like Google, Microsoft, Salesforce, and Amazon, Posh competes with a number of startups in the expanding call center automation space. Yellow.ai, a chatbot platform headquartered in Bangalore, India, recently raised $78 million in venture capital to expand its platform globally. There’s also Ada, a Toronto-based startup developing AI-imbued customer service chatbots.

Grand View Research anticipates that the global contact center software market will be worth $90.6 billion by 2028, if the current trend holds.

Posh Technologies | Enterprise Conversational AI

Kashyap argues that Posh’s focus on the financial services industry gives it an advantage over rivals targeting a broader range of segments. To date, Posh has partnered with more than 50 financial institutions to deploy web-based and mobile-based digital agents, and the company’s software handles tens of thousands of chats per day and reaches over 5.5 million people.

“We serve approximately 50 community financial institutions — banks and credit unions — across the U.S. and their end users and members. Our digital assistants and voice banking assistants handle tens of thousands of requests a day on behalf of these financial institutions,” Kashyap said. “We are very focused on financial services and thus train our AI models to be very domain-focused. Not only are we focused on training models with the goal of automating routine banking inquiries and workflows, we’re also using AI to glean insights from conversations that pass through our system — for example, uncovering operational root causes or detecting anomalies.”

Going forward, Canapi Ventures partner Neil Underwood expects that 40-employee Posh will benefit from expanded access to credit unions, banks, and prospective talent through its other backers Curql Collective, CMFG Ventures, JAM Fintop, Human Capital, and Piedmont. In the coming months, Posh plans to ramp up hiring to keep pace with what it describes as “surging” demand.

“Beyond answering questions, Posh has developed a competency in helping banks complete simple banking transactions. Especially for credit unions, who are highly focused on member experience, this can be a meaningful value add,” Underwood told VentureBeat via email. “Over time, we anticipate that the Posh platform will be used by credit unions and banks to drive entire banking interactions.”

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AI

Report: AI startup funding hits record high of $17.9B in Q3

Even as economies struggle with the chaos of the pandemic, the AI startup space continues to grow stronger with increased investments and M&A deals.

According to the latest State of AI report from CB Insights, the global funding in the segment has seen a significant surge, growing from $16.6 billion across 588 deals in Q2 2021 (figures show $20B due to the inclusion of two public subsidiary fundings) to $17.9 billion across 841 deals in the third quarter. Throughout the year (which is yet to end), AI startups around the world raised $50 billion across 2000+ deals with 138 mega-rounds of 100+ million. As much as $8.5 billion of the total investment went into healthcare AI, $3.1 billion went into fintech AI, while $2.6 billion went into retail AI.

The findings show how AI has become a driving force across nearly every industry and is drawing significant attention from VCs, CVCs, and other investors. In Q3 alone, there were 13 new AI unicorns globally, bringing the total number of billion-dollar AI startups to 119. Three startups also reached $2 billion in valuation — Algolia and XtaPi from the U.S. and Black Sesame Technologies from China.

Meanwhile, in terms of M&A exits, the quarter saw over 100 acquisitions like the previous one, putting the total exits for the year at 253. The biggest AI acquisition of the quarter was PayPal snapping up Paidly — a company determining creditworthiness using AI/ML — for $2.7 billion, followed by Zoominfo’s acquisition of Chorus.ai — a startup using AI to analyze sales calls — for $575 million.

U.S. AI startups continue to dominate

State of AI startup funding

Out of the $17.9 billion raised by AI startups worldwide in Q3, a significant $10.4 billion went to companies based in the U.S. and $4.8 billion into those in Asia. However, Asian firms raised this amount in nearly just as many deals (321) as in the U.S. (324), which signals that the average deal size was smaller there compared to U.S. Mega-round deals in the U.S. stood at 24 in Q3, while Asia saw 13 such deals.

Databricks, Dataiku, Olive, XtalPi, Datarobot, and Cybereason were the companies with the biggest rounds in the U.S. in the third quarter.

As compared to Asia and the U.S., funding in Canada, Latin America, and Europe regions was the lowest at $0.4 billion, $0.5 billion, and $1.6 billion, respectively. These regions cumulatively saw just eight mega-rounds.

Read the full report here.

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US sanctions a Chinese surveillance company with Silicon Valley funding

The US Department of Commerce has sanctioned 14 Chinese tech companies over links to human rights abuses against Uyghur Muslims in Xinjiang, including one backed by a top Silicon Valley investment firm.

DeepGlint, also known as Beijing Geling Shentong Information Technology Co., Ltd., is a facial recognition company with deep ties to Chinese police surveillance, and funding from US-based Sequoia Capital. Today the Commerce Department added it to its Entity List, which restricts US companies from doing business with listed firms without a special license. Sequoia did not immediately respond to a request for comment.

DeepGlint co-founded a facial recognition lab in 2018 with Chinese authorities in Urumqi, the capital of Xinjiang, according to the South China Morning Post. It has also gained international bragging rights through the US National Institute of Standards and Technology’s (NIST) Face Recognition Vendor Test. DeepGlint claimed top accuracy in the test as of January 2021, giving it a potent marketing tool in the security and surveillance industry.

While DeepGlint has been accepted for a public offering on Shanghai’s STAR stock exchange, the firm hasn’t seen the commercial success of other AI startups in the country, explained Jeffrey Ding in his ChinAI newsletter last month. Since the firm is so heavily invested in government work, it has to follow slow government procurement cycles and is unlikely to score huge infrastructure projects, Ding writes.

Sequoia Capital has funded another company that later ended up on the Entity List. In 2020, Sequoia-backed Yitu Technology was added to the list for similar human rights abuses. Sequoia invested in DeepGlint back in 2014, before China’s genocide of Uyghurs had come to light. (The same year, Bill Gates also referred to the startup as “very cool,” according to KrAsia.)

The Commerce Department also sanctioned Xinjiang Lianhai Chuangzhi Company and Chengdu Xiwu Security System Alliance, two subsidiaries of Chinese military contractors. They both offer surveillance equipment and services, according to their websites and academic reports. Xinjiang Lianhai Chuangzhi Company created an AI-powered checkpoint system that is able to track Uyghurs as they move around cities, according to a report from the Italian Institute for International Political Studies.

Another firm sanctioned today is Leon Technology, a surveillance company that was controlled by Chinese AI giant SenseTime until its role providing oppressive technology in Xinjiang was reported in 2019. SenseTime then divested its 51 percent stake in it.

The Commerce Department sanctions also included nine other Chinese companies for national security reasons, as well as companies in Iran, Russia, and Canada, among other countries.

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AI

Ground freight logistics startup Flock Freight closes $215M funding round

Digital freight logistics company Flock Freight today announced that it raised $215 million in series D funding led by Softbank Vision Fund 2, increasing the startup’s valuation to $1.3 billion. The round also included participation from Susquehanna Private Equity Investments, LLLP, Eden Global Partners, SignalFire, GLP Capital Partners, and GV (formerly Google Ventures), and will be used to support the development of Flock Freight’s technology and to expand the company’s talent and operations, according to CEO Oren Zaslansky.

Pandemic-related demand and disruptions have put an immense strain on the supply chain. DAT Solutions found that shippers’ requests for moving goods increased by 577% from April 2020 to April 2021, while postings of trucks available to move goods were down 17%. Meanwhile, ecommerce sales continue to experience outsized growth, with online penetration remaining approximately 35% above pre-pandemic levels, according to McKinsey.

Founded in 2015 by Zaslansky, Flock Freight hosts a marketplace that pools less-than-truckload (LTL) and partial-truckload (PTL) freight shipments so that they can be shipped via a full truckload service. For LTL, Flock Freight facilitates the travel of shipments on trucks to their intended destinations, eschewing the traditional hub-and-spoke freight transit model. In the case of PTL, the platform finds as many as ten trucks along a single route and pools them into a single truckload to maximize savings.

“I’ve been in the trucking and logistics industry for more than 20 years since I founded E&H Transport Network in 1996. I built E&H from the ground up, including the recruitment and onboarding of over 1,000 truck drivers,” Zaslansky told VentureBeat via email. “In 2001, I founded SolSource Logistics, a third-party logistics company serving international Fortune 1000 clients such as Whole Foods, Wegmans Grocery, and Sprouts Market. In serving a diverse customer base in the transportation industry, I identified an unmet need to reduce the significant waste and antiquated approach to transportation. Too often, assets are underutilized and freight moves through intermediary depots when otherwise technology could facilitate those solutions without the waste of brick and mortar.”

Flock Freight also offers instant “prebates” that lower contracted truckload rates when shippers have freight that measures 44 feet or less. With this program, Flock Freight automatically moves eligible freight with shared truckload shipping, ostensibly delivering same-quality truckload service at more palatable prices.

Flock Freight

“Flock Freight’s machine learning-based product, FlockDirect, pools less-than-truckload freight consisting of a few pallets together to create full truckloads. It optimizes routes by pooling freight heading in the same direction so that trucks only stop at each drop-off, avoiding traditional terminals,” Zaslansky explained. “To create shared truckloads, Flock’s pooling algorithms sift through an enormous number of possible shipment permutations to find only those which are feasible to execute and economically advantageous for all parties. A ‘combinatorics explosion’ takes place when Flock Freight takes the hundreds of partial size freight shipments it receives per day and uses its complex algorithm to pool them together onto single trucks — combining three to five partial loads and taking into account numerous variables such as destination, timing, product type (food vs. chemicals), and more. For 500 shipments, the possible pooling combinations exceed 62 billion, to put numbers in to show the scale.”

Disrupting competition in the freight industry

Flock Freight claims its driver network in the U.S. and Canada numbers are in the thousands, and each individual driver can be tracked in real time via a dashboard or email notifications. The company says its damage claim rate is a low 0.001% and its on-time delivery rate is 97.5%. It also says it is able to reduce fuel emissions by up to 40% by eliminating the need to switch trucks or stop at warehouses.

“Flock Freight has pooled close to 20,000 shipments … Additionally, Flock Freight’s hubless pooling product has attracted new customers in 2020, including mid-market and enterprise companies such as Berlin Packaging, Blue Diamond Almonds, Mueller Industries, Nature’s Bounty, and Tuft & Needle,” Zaslansky said. “The company has tripled its workforce in 2021 and plans to add even more talent to its Encinitas headquarters and new Chicago location this year, and additional plans to hire more than people in 2022.”

Zaslansky argues that those stats set it apart from competitors in the freight logistics space. Uber offers a service called Uber Freight, to which it recently committed another $200 million as part of a major expansion. San Francisco-based startup KeepTruckin has secured hundreds of millions to further develop its shipment marketplace. Next Trucking last year closed a $97 million investment. Meanwhile, Convoy raised $400 million at a $2.75 billion valuation for a platform that it asserts makes freight trucking more efficient.

“Flock Freight is disrupting the $2 trillion freight industry because it is doing something that no other company has been able to do: fundamentally change the way the industry operates. While digital freight brokerages, such as Convoy, Uber Freight, and Transfix, automate and streamline the connection between shippers and carriers, Flock Freight is the only company changing the way freight gets transported with a whole new mode of shipping,” Zaslansky said. “Our business has grown in spite of the pandemic, not because of it. Because we offer faster shipping times all while protecting shipments from damage, our customers are recognizing and experiencing the power of our shared truckload technology.”

Solana Beach, California-based Flock Freight — which has raised $399 million to date and is on track to hit 325% year-to-date revenue growth — plans for an initial public offering in the next 18 to 36 months.

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Nvidia is tracking more than 8,500 AI startups with $60B in funding

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Nvidia is tracking more than 8,500 AI startups through its Inception AI startup program. Those companies have raised more than $60 billion in funding and come from 90 countires, Nvidia said.

Based on estimates from market researcher Pitchbook, the Nvidia numbers represent roughly two thirds of all AI startups. Overall, Nvidia believes there are about 12,000 AI startups in the world.

“It’s a good picture of the landscape,” said Serge Lemonde, global head of Nvidia Inception, in an interview with VentureBeat.

Across the startups, the definition of an AI company is changing, as many companies across all industries are adopting AI. There are new uses of AI emerging as companies adopt deep learning neural networks. The Inception companies now include more than high-performance computing, graphics, and other common startups.

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“The fastest growing segments or verticals in the healthcare itself are around pharma and AI biology,” Lemonde said. “We launched the program in 2016. And every year, it’s been growing faster. In 2020, we had a plus 26% growth in the number of members joining Inception, and just this first half of this year is already plus 17%. So AI adoption is impacting every industry.”

The Inception program provides assistance and software for AI startups, and it’s Nvidia’s way of introducing AI companies to its hardware products such as its AI chips. The data from the ecosystem gives the companies a lot of insights into the AI economy.

Regional strengths

Nvidia's Inception program tracks AI startups.

Above: Nvidia’s Inception program tracks AI startups.

Image Credit: Nvidia

The U.S. leads the world with nearly 27% of the Inception AI startups. Those U.S. companies have raised more than $27 billion. And of the U.S. startups, 42% are based in California. That means more than one in 10 AI startups are based in California, with 29% in the San Francisco Bay Area. This underscores the draw of Silicon Valley for startup founders and VC funding, Lemonde said.

Following the U.S. is China, in terms of both funding and company stage, with 12% of Nvidia Inception members based there. India comes in third at 7%, with the United Kingdom right behind at 6%.

Taken together, AI startups based in the U.S., China, India and the U.K. account for just over half of all startups in Nvidia Inception. Following in order after these are Germany, Russia, France, Sweden, Netherlands, Korea and Japan.

Industry focus

In terms of industries, healthcare, information technology services (IT), intelligent video analytics (IVA), media and entertainment (M&E) and robotics are the top five in Nvidia Inception. AI startups in healthcare account for 16% of Inception members, followed by those in IT services at 15%.

AI startups in IVA make up 8%, with M&E and robotics AI startups tied at 7%.

Recent growth

Nvidia's Inception AI startups are from the green countries.

Above: Nvidia’s Inception AI startups are from the green countries.

Image Credit: Nvidia

More than 3,000 AI startups have joined Nvidia Inception since 2020. Similar to data across Inception as a whole, AI startups from the U.S. account for the largest segment (27 percent), followed by China (12 percent), and India and the U.K. (tied at 6 percent).

“Some countries are accelerating their ecosystem of AI startups by investing money and encouraging the local players to create more companies,” Lemonde said. “We saw India growing these last couple of months, and so India is definitely now the third country with 7% of the AI startups in the world.”

Additionally, startups that have joined since 2020 are concentrated in the same top five industries, though in slightly different order. IT services leads the way at 17%, followed by healthcare at 16%, M&E at 9%, IVA at 8% and robotics at 5%.

Within the top two industries —  healthcare and IT services — there’s more detail among AI startups who have joined since 2020. The dominant segment within IT services is computer vision at 27%, with predictive analytics in second place at 9%. The top two segments in healthcare are medical analytics at 38% and medical imaging at 36%, though the fastest growth is among AI startups in the pharma and AI biology industries at 15%.

Virtual and augmented reality startup companies are far outpacing any other segment within M&E, mostly due to the pandemic. These startups are coming to Nvidia Inception with a shared vision of building an ecosystem for the metaverse, the universe of virtual worlds that are all interconnected, like in novels such as Snow Crash and Ready Player One.

Healthcare AI startups skyrocketed during the pandemic as well, with growth in medical imaging and more.

“Now it’s about biology, pharma, DNA, and more,” Lemonde said. “I think there is a lot of growth there as well. We saw during COVID new verticals grow fast like virtual reality and augmented reality. We saw the usage of AI go up but this metaverse shared vision in many countries grow up.”

Growing regional hubs

Above: Regional Advantage by Annalee Saxenian studied the rise of Silicon Valley over Boston.

Image Credit: Annalee Saxenian

Since Inception’s launch in 2016, it has grown more than tenfold. This growth has accelerated year over year, with membership increasing to 26% in 2020, and already reaching 17% in the first half of 2021.

To grow a big AI hub in a region, Lemonde believes it’s most important to have good universities and educational infrastructure in a region.

“If you look at the top countries, the governments push technology, invest in science and AI, invest computing infrastructures in their countries, and push for investments,” he said.

Nvidia Inception is a program built to accommodate and nurture every startup that is accelerating computing, at every stage in their journey. All program benefits are free of charge. And unlike other accelerators or incubators, startups never have to give up equity to join. After the startups graduate from Inception, Nvidia hands them off to its developer relations and sales departments.

“In our program, what we are looking at is to help them all,” Lemonde said. “The lesson here is really having this window on the landscape and helping the startups all around the world is helping us understand at the new trends. We can help more startups by developing our software  and platforms for the upcoming trends.”

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AI startup funding remained strong in Q2, report finds

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The pandemic spurred investments in AI across nearly every industry. That’s according to CB Insights’ AI in the Numbers Q2 2021 report, which found that AI startups attracted record funding — more than $20 billion — despite a drop in deal volume.

While the adoption rate varies between businesses, a majority of them — 95% in a recent S&P Global report — consider AI to be important in their digital transformation efforts. Organizations were expected to invest more than $50 billion in AI systems globally in 2020, according to IDC, up from $37.5 billion in 2019. And by 2024, investment is expected to reach $110 billion.

The U.S. led as an AI hub in Q2, according to CB Insights, attracting 41% of AI startup venture equity deals. U.S.-based companies accounted for 41% of deals in the previous quarter, up 39% year-over-year. Meanwhile, China remained second to the U.S., with an uptick of 17% quarter-over-quarter.

AI startup funding in Q2 was driven mostly by “mega-rounds,” or deals worth $100 million or more. A total of 24 companies reached $1 billion “unicorn” valuations for the first time, and AI exits increased 125% from the previous quarter, while AI initial public offerings (IPO) reached an all-time quarterly high of 11.

Unicorn valuations

Cybersecurity and processor companies led the wave of newly minted unicorns, with finance and insurance and retail and consumer packaged goods following close behind. On the other hand, health care AI continued to have the largest deal share, accounting for 17% of all AI deals in Q2.

Overall mid-stage deal share — i.e., series B and series C — reached an all-time high of 26% during Q2, while late-stage deal share — series D and beyond — remained tied with its Q1 2021 record of 9%. But the news wasn’t all positive. CB Insights found that seed, angel, and series A deals took a downward trend, making up only 55% of Q2 deals, with corporate venture backing leveling out. Just 39% of all deals for AI startups included participation from a corporate or corporate venture capital investor, up slightly from 31% in Q1 2021.

CB Insights

But CB Insights says that the rise in AI startup exits in Q2 reflects the strength of the sector. “The decline of early-stage deals and increase of mid- and late-stage deals hint at a maturing market — however, early-stage rounds still represent the majority of AI deals,” analysts at the firm wrote. “Plateauing [corporate] participation in AI deals may reflect a stronger focus on internal R&D or corporations choosing to develop relationships with AI portfolio companies instead of sourcing new deals.”

Experts predict that the AI and machine learning technologies market will reach $191 billion by the year 2025, a jump from the approximately $40 billion it’s valued at currently. In a recent survey, Appen found that companies increased investments by 4.6% on average in 2020, with a plan to invest 8.3% per year over the next three years.

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AI diversity groups snub future funding from Google over staff treatment

Google’s AI ethics drama has taken another twist. Three groups working to promote diversity in AI say they will no longer accept funding from the search giant after a series of controversial firings at the company.

Queer in AI, Black in AI, and Widening NLP cited the dismissals of Timnit Gebru and Margaret, the former co-leads of Google’s Ethical AI team, as well as recruiter April Christina Curley, as reasons for the decision.

Ia joint statement issued on Monday, the groups said Google’s actions had “inflicted tremendous harm” and “set a dangerous precedent for what type of research, advocacy, and retaliation is permissible in our community.”

Until Google addresses the harm they’ve caused by undermining both inclusion and critical research, we are unable to reconcile Google’s actions with our organizational missions.We have therefore decided to end our sponsorship relationship with Google.

Gebru was sacked in December after a conflict over a research paper she co-authored about the dangers of large language models, which are crucial components of Google’s search products.

[Read: 3 new technologies ecommerce brands can use to connect better with customers]

Mitchell was fired three months later for reportedly using automated scripts to find emails showing mistreatment of Gebru, while Curley says she was terminated because the company was “tired of hearing me call them out on their racist bullshit.”

The three groups said Gebru and Mitchell’s exits had disrupted their lives and work, and also stymied the efforts of their former team. Curley’s departure, meanwhile, was described as “a step backward in recruiting and creating inclusive workplaces for Black engineers in an industry where BIPOC are marginalized and undermined.”

The groups urged Google to make the changes necessary to promote research integrity and transparency, as well as allow research that is critical of the company’s products.

They also called for the tech giant “to emphasize work that uplifts and hires diverse voices, honors ethical principles, and respects Indigenous and minority communities’ data and sovereignty.”

None of the organizations have previously rejected funding from a corporate sponsor. Wired reports that Queer in AI received $20,000 from Google in the past year, while Widening NLP got $15,000.

The trio joins a growing number of individuals and organizations who have spurned funding from Google over the company’s treatment of staff.

Five months after Gebru’s firing, the fallout continues to harm Google’s reputation for AI research.

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AI

Upsolver enables no-code data analytics in the cloud with $25M funding

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Upsolver, a no-code startup that enables analytics on cloud data lakes, this morning announced that it raised $25 million in financing led by Scale Venture Partners. The company, which also today launched a free community edition of its product, says the funds will be used to hire engineers and scale its go-to-market efforts.

Enterprises are rapidly adopting the cloud — 68% of CIOs ranked migrating to the cloud as their top IT spending driver in 2020, according to a Deloitte survey. But building an analytics-ready cloud data lake can be complex and expensive. A recently published Statista report found that around 83% of cloud practitioners considered security, managing cloud spend, governance, and a lack of resources to be significant barriers to entry.

Upsolver develops software designed to prime data lakes for analytics, CEO Ori Rafael told VentureBeat via email. Founded in 2014 by Rafael and Yoni Eini, the company’s platform offers a visual structured query language (SQL) interface and automations for data optimization, tuning, and orchestration.

“We wanted to store data affordably in the cloud without analytics vendor lock-in,” Rafael said. “Unfortunately, what used to take three hours using SQL turned into 30 days of hand-coding and complex Spark configuration. We created Upsolver to bridge this gap between raw cloud data and analytics-ready data.”

Upsolver

Upsolver’s product lets companies perform analytics using a range of query engines and data systems including PrestoDB, Trino, Athena, Snowflake, Redshift, Synapse Analytics, Splunk, and Elastic. Ultimately, the goal is to replace all a customer’s code-heavy approaches with Upsolver’s compute layer, which sits between the customer’s cloud storage and their preferred tools, engines, and apps.

“Upsolver is a critical component for successfully implementing a cloud data lake for analytics, which is a popular approach due to the affordability that data lakes provide. We complement cloud data warehouses, search engines, and other purpose-built data stores as well,” Rafael said. “Upsolver is often used to output prepared data to those platforms making data available to standalone query engines. Data engineers use Upsolver’s visual user interface to build any data transformations and preparation tasks. This generates SQL that the data engineer can also directly edit to fine-tune the processing.”

Rafael says that Upsolver will soon add the ability to replicate databases into data lakes while keeping them up to date. The platform recently launched on Azure and is set to become available in a community edition delivering “free-forever” capabilities to those with smaller workloads, providing a proving ground for companies who might want to work with Upsolver on larger use cases.

Scale partner Ariel Tseitlin asserts that Upsolver benefits from having a foot in two fast-growing markets: big data analytics and data lakes. The global data lake market size was valued at $7.6 billion in 2019, according to Grand View Research. And in 2017, Forbes reported that 53% of companies had adopted big data analytics, with a large portion opting to run workloads in the cloud.

Thirty-employee Upsolver says that revenue tripled 2020 as brands including Cox Automotive, Wix, and AppsFlyer joined its customer base.

“Monolithic analytics platforms are a thing of the past. Today’s organizations require a variety of analytics tools to fully capitalize on their data,” Tseitlin said in a press release. “Data lakes originally promised this variety and openness but also required a large, ongoing investment in engineering. Upsolver eliminates this trade-off.”

Existing investors Vertex Ventures US, Wing Venture Capital, and JVP also participated in Upsolver’s series B round. It comes on the heels of a $13 million series A and brings the company’s total raised to date to $42 million.

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Tech News

Amid the live audio app boom, Clubhouse is reportedly seeking funding with a $4B valuation

Since Clubhouse became the new social media darling in just a few short months, live audio features and platforms have garnered a lot of interest in the tech community. The company now wants to raise more money, which should help it stay ahead of the competition.

According to a report from Bloomberg, Clubhouse wants to start new funding round, with the firm valued at $4 billion.

In January, the live audio platform raised $100 million in funding led by Andreessen Horowitz;the VC giant had valued the app at $1 billion at that time. The new round might quadruple the net worth of the company.

Bloomberg noted that it’s not clear how much money the company wants to raise at the moment, so terms of the deal and final valuation could change.

Clubhouse is facing heated competition from tech companies who are trying to integrate live audio into their platforms. Twitter‘s Spaces feature is already available to many users, and it has ambitions to expand to desktop too.

Discord launched a real-time audio chat feature last month, and LinkedIn and Slack have said they’re building something on similar lines. Last month, Spotify acquired Locker Room, a live conversation apps for discussing Sports, and aims to introduce new experiences in its app. Meanwhile, Facebook is reportedly working on a Clubhouse-like product too.

Amid all this live audio frenzy, Clubhouse might want to solidify its position as the pioneer of the field, and roll out unique features to retain and grow its users. Earlier this week, the company launched a payments feature that lets you send money to creators you like.

Published April 7, 2021 — 05:23 UTC



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