Technology
Global VC activity declines in Q3 | NVCA 1st look
Global venture capital activity declined in Q3, confirming that 2024 will be another weak year for venture investments and exits, according to the Q3 2024 Pitchbook/NVCA Venture Monitor First Look.
By just about every number, Q3 was weak and 2024 overall doesn’t compare well in terms of numbers of deals, average deal size, VC fundraising, exits and dollar amounts raised. No particular region stood out in terms of great performance, based on the report from Pitchbook and the National Venture Capital Association.
PitchBook’s lead VC analyst Kyle Stanford said in a statement that dealmaking in the U.S. showed its first quarter-over-quarter decline in a year. Just an estimated 3,777 VC investment deals were completed during the quarter, falling back to pre-2021 levels.
The median valuations for these stages is high, but there has been upward pressure on the figure due to previous high multiple valuations for companies now finally coming back to raise again. Deal value during Q3 was lowest of the year due to few outsized rounds being raised. Median deal sizes have also seen an
uptick from 2023, but they remain well below the median from 2021. Stronger companies raising capital are receiving larger deals to help weather the market slowdown.
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Exits continued to find little in terms of success in the market. Just 10 companies went through a public listing in the U.S., and $11.2 billion in total exit value was created during the quarter. The large number of companies that remain stuck in the private market are weighing on distributions back to limited partners, which causes further challenges within VC.
Stanford said, in perhaps the only bright spot, was that the rate cut from the Federal Reserve in September is a good step to balancing costs of borrowing and relieving pressure on public markets that
could help begin the registration process for companies moving forward. M&A remains slow, due to both regulatory pressures and market conditions.
With one quarter left, 2024 is pacing for the second slow year. Just $64.0 billion has been raised across U.S. VC funds. The low commitments are connected to the low distributions and poor returns that the strategy has provided over the past few years. Although fundraising figures are on par with 2020, the number of companies currently private, VC-backed adds strain to capital resources for the market. LPs have committed a large proportion of the capital to established managers and large funds, which consolidates opportunities for companies, and investment decision making with fewer groups.
Pitchbook’s VC analyst Nalin Patel said that in Europe in Q3 2024, VC deal activity was slightly down from the second quarter. Despite an uptick in deal value in Q2, Q3 marked a slight dip. Nonetheless, activity has stabilized since declining from peaks. Deal counts were marginally down QoQ, further demonstrating that fewer deals are closing as investors remain selective about their investments. There are encouraging signs heading into the end of 2024, with monetary policy loosening and inflation rates normalizing.
Exit value through Q3 2024 has surpassed the annual figure from 2023, providing optimism within markets. Major VC-backed exits in the past two years have been scarce and a rebound could be on the horizon if public markets pick up. Risk remains a key consideration for exits in terms of valuation, returns, and volatility. Founders and investors would not want to lose significant amounts of value from portcos that has been built up over several years.
The fundraising run rate through Q3 2024 is tracking flat from the 2023 full-year showing. Macroeconomic conditions as well as the tough exit environment have made fundraising tricky. Larger funds have closed in 2024 but capital remains locked into portfolio companies that could be due an exit. We could see fundraising increase in 2025 if exits pick up and capital is recycled back into VC funds.
In Asia, Stanford said venture activity continues its slow 2024. Just $14.9 billion was invested during the
quarter, the lowest figure since Q1 2017. The deep decline of China’s venture market has had a major impact on the overall financing market. Other markets such as India and Southeast Asia have not kept up pace, either. Asia deal count in Q3 (2,143) was less than half the high mark in Q4 2021 (4,704), Stanford said.
Asia supported the highest exit value of any region in Q3, boosted by the IPO of India’s Ola Electric, which added more than $3 billion to the figure. Four of the top six largest exits of the quarter occurred in Asia, all IPOs.
Asia’s fundraising has remained subdued, with just $53.1 billion committed to the strategy within the Asia markets in during the first three quarters of the year. 2024 will likely close on par with 2023’s fundraising total of $84.8 billion. That would make the past two years the only years under $100 billion in total commitments for Asia since 2017.
And in Latin America, Stanford said dealmaking activity has been slow through Q3, a drag being that much of the high activity levels were reliant on non-domestic investors that have pulled back to their classic strategies and investment geographies. The lack of exits by Latin American companies has increased the risk of investments in the market. Just $1.0 billion was invested in the market during Q3, and the year is paced for just over $4 billion in total investment.
Similar to, but more exacerbated than the rest of the world, fundraising has been hurt by the lack of exits and low distributions coming back to LPs. Because of this higher risk, LPs have looked to diversify into other markets or strategies. Just 10 funds have been closed in Latin America during the year. The year may become the lowest for total commitments in the past decade.
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Technology
Oura’s return to the smart ring fight
Oura’s next-gen ring appears to be an upgrade in every way. It features a sleeker design, longer battery life and smarter sensors to offer deeper insights for wearers. No more squarish edges; it’s a perfect ring this time. Oura says Ring 4 has 18 signal pathways, up from eight in the Gen3, which is paired with its new Smart Sensing algorithm.
New features include automatic heart rate and activity detection for up to 40 activities. It’ll land in six colors: Silver, Brushed Silver, Gold, Rose Gold, Stealth and Black. All bar the Stealth is made of titanium. Oura Ring 4 is available to pre-order today, with shipping expected to begin on October 15, 2024. Prices start at $349.
— Mat Smith
The biggest stories you might have missed
OpenAI rakes in over $6 billion in new funding
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Through an Instagram stream and publicly available information.
Two Harvard students used facial recognition tech and a large language model to unearth a subject’s name, occupation and other details. Their setup (dubbed I-XRAY) can use that information to pull data like addresses, phone numbers, family member details and partial social security numbers from various sources online.
In a demo video, AnhPhu Nguyen and Caine Ardayfio used the glasses to address people who appear to be strangers by name, discuss their work and bring up a place where they may have met in the past, based on information picked up. The students told 404 Media they developed I-XRAY to make people aware of what’s possible with current technology — they won’t release the code they used.
The long-awaited SUV is finally here.
Following its first two cars of the same name, the Polestar 3 delivers what many of us were looking for. It’s a mass-market machine to fill the needs and wants of buyers looking for an all-electric SUV with proper dimensions — and yellow seat belts. After all the delays, we’ve got a test drive.
The new minimum price for a Model 3 is $42,500.
Tesla’s Model 3 Standard Range Rear-Wheel Drive is no longer available in its online configurator. Electrek first reported on the absence of the cheapest option from the electric vehicle brand, with a price tag of $39,000. Now the Model 3 with Long-Range Rear-Wheel Drive takes that title with a retail price of $42,500.
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Inference framework Archon promises to make LLMs quicker, without additional costs
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Researchers from Stanford University‘s Scaling Intelligence Lab introduced a new inference framework that could help large language models (LLMs) go through potential responses faster.
The framework, Archon, uses an inference-time architecture search (ITAS) algorithm to improve LLMs performance without additional training. It is model agnostic, open-source and designed to be plug-and-play for large and small models.
Archon could ideally help developers design AI model systems using multiple inference-time techniques to cut down on models to determine responses. The Scaling Intelligence Lab said techniques like Archon would help cut down on costs related to building models and inference. As LLM development turns toward larger parameters or more advanced reasoning, costs could increase despite companies like OpenAI anticipating more affordability.
According to the researchers, Archon automatically designs architectures that improve task generalization, enabling models to perform tasks beyond those they were initially trained on.
“Our Archon framework and ITAS algorithm draw inspiration from neural architectures and neural architecture search, respectively,” the researchers said in their paper. “Archon is constructed of layers of LLMs, in which models in the same layer run in parallel but each later runs sequentially.”
These layers perform different inference-time techniques, “either transforming the number of candidate responses through generation and fusion (like linear transformations) or reducing the number of candidate responses to improve quality (like non-linearities).”
Archon outperformed GPT-4o and Claude 3.5 Sonnet by 15.1 percentage points in benchmark tests such as MT-Bench, Arena-Hard-Auto, Alpaca-2.0 Eval, MixEval, MixEval Hard, MATH and CodeContests. When Archon faced open-source LLMs, it outperformed them by 11.2 percentage points.
Archon components
The ITAS algorithm is comprised of several LLM components and can do inference-time techniques.
The first component is the Generator, which creates possible answers for the model. The second component, the Guser, will take these responses and combine them into one. An example would be if the question posed to a model wants to know the capital of France, the fuser will take the generated responses of “the capital of France is Paris,” France is in Europe,” and turn it to “the capital of France, a country in Europe, is Paris.”
Next, Archon moves to the Ranker component, which ranks the best answers. A Critic component evaluates the ranked answers to determine whether they’re good or bad. The Verifier checks for logic and correctness before moving on to the Unit Test Generator and Evaluator, which do small tests to see if the response works and check the test results.
By building Archon this way, the researchers said the framework improves the quality of LLMs’ responses faster and without additional fine-tuning.
Archon’s limitations
So far, the Archon framework works best with LLMs with 70B parameters or more like Meta’s Code Llama 70B, making it difficult to point to most LLMs right now. The researchers said most of the challenge comes from the smaller model’s limited capabilities to follow instructions due to the smaller context windows.
“When we utilize the Archon architecture with only 7B open-source models, we get a notable decrease of 16%,” in performance, the paper stated.
Smaller models using the Archon framework lagged behind single-turn models by 15.7%.
The Stanford lab also said Archon “is not ideal for tasks that prefer the latency of a single LLM call,” such as chatbots. The framework makes multiple LLM calls because of the different operations it does so single question-and-answer queries won’t benefit from its capabilities. Archon may work better for tasks involving complex instructions like solving equations, programming, or even complicated customer service issues.
Despite its limitations, the researchers behind Archon said they hope it can accelerate the development of high-performing models without requiring more inference and training capital.
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Technology
Instant harkens back to a pre-Google Firebase
Instant wants to recapture some of the magic of the pre-Google-acquisition Firebase by building a modern, Postgres-based open source version of it.
Like the original Firebase, San Francisco-based Instant focuses on giving front-end developers easy access to a real-time database with offline capabilities without the need to manage any of the back-end architecture. The service supports applications written in React, React Native, and vanilla JavaScript. In addition to the database, it also offers tools to manage authentication and permissions, as well as real-time features like shared cursors, presence, and more.
The team recently open sourced the project.
Instant was founded by former roommates Joe Averbukh (CEO) and Stepan Parunashvili, who previously worked at companies like Wit.ai, Facebook, Airbnb, and others.
At Facebook, Averbukh told me, the architecture was set up to ensure that as a front-end engineer, he was able to move quickly. Meanwhile, at Airbnb, the company’s intricate microservices architecture meant it took a long time to try a new idea. “Thankfully, we already had Firebase inside Airbnb, and we could use it for notifications. So we would actually just use Firebase to prototype these ideas — and that was a huge win,” he explained.
Before starting Instant, the co-founders worked on a fitness app, based on Google’s Firebase. While they loved all of the features like optimistic updates and offline mode that Firebase offers out of the box, they missed having access to a relational database since Firebase’s focus is on its NoSQL database.
“You see apps like Figma, Notion, and Linear — they’re winning the market because of this feature set that they have,” Averbukh said. “And we think that basically, in the same way that apps today are much better than apps before, the expectations are going to rise for what people want in their apps. But the reality is, the way that people build these features today is that they have this whole team that’s building all of these sync services.”
At the core of all of this is Aurora, AWS’s relational database service, which is cost-effective and allows Instant to quickly spin up new databases inside of a multi-tenant architecture that still offers strong security guarantees. Averbukh argues that competitors like Supabase have to spin up a new database for every project (and free user), while Instant essentially lives in one large Postgres instance. He also stressed that if a large enterprise customer would sign up for the service, the team could offer them to spin them up a separate database.
On Wednesday, the company announced that it has raised a $3.4 million seed funding round. It’s backed by Y Combinator and SV Angel, as well as prominent angel investors like former Firebase CEO James Tamplin, Paul Graham, Greg Brockman, and Jeff Dean.
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Technology
A Bank of America outage showed customers blanked-out account balances
First, it was Spotify, then Verizon, then PlayStation, and now it’s apparently Bank of America’s turn to have an outage this week. Some customers reported problems accessing their bank accounts on Wednesday, with the balances showing $0 or “—-” instead of what should be there.
“Some mobile and online banking clients experienced an issue accessing their accounts and balance information earlier today,” writes Bank of America media relations executive Matt Card in an email to The Verge. “These technology issues have been fully resolved. We apologize for any inconvenience.”
Reports spiked just before 1PM ET on Downdetector, with posts across X and Reddit from people reporting that their account balances don’t show anything (some mentioned that the amounts they owe, however, appear to be displaying accurately).
We verified this afternoon that the bank’s app was showing customers a notification that “Accounts temporarily unavailable” and that “Some accounts and/or balances are temporarily unavailable,” as reported previously by CNN. Some people have reported their accounts are working or intermittently gaining access to their information, and it’s unclear how many people have been affected. In July, Bank of America said 58 million clients use its “digital capabilities to help manage their financial lives” and that they connected a record 23.4 billion times last year.
There’s no word on what might have caused the problem, but let us know if things are working for you now.
Update, October 3rd: Added updated Bank of America statement.
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