Pinecone announces $28M Series A for purpose-built database aimed at data scientists
When Pinecone launched last year, the company’s message was around building a serverless vector database designed specifically for the needs of data scientists. While that database is at the core of what the company is doing, it is moving towards a more refined use case for that database around AI-driven search, helping those data scientists find the proverbial needle in the haystack.
When we spoke to Pinecone founder and CEO Edo Liberty last year at the time of his $10 million seed round, his company was just feeling its way, building out the database. He came from Amazon where he helped build the SageMaker database service. He says that they have come a long way since then.
“A lot has changed since our seed announcement, so first and foremost we launched our proper production paid service in October, and it’s been growing rapidly both in adoption and revenue since, and so things are going really well,” Liberty said.
He described the reason for a purpose-built database for data scientists at the time of the seed funding this way:
“The data that a machine learning model expects isn’t a JSON record, it’s a high dimensional vector that is either a list of features or what’s called an embedding that’s a numerical representation of the items or the objects in the world. This [format] is much more semantically rich and actionable for machine learning,” he explained.
He says that today that semantically rich approach is driving customers to use Pinecone.”The predominant use of the vector databases is for search, and search in the broad sense of the word. It’s searching through documents, but you can think about search as information retrieval in general, discovery, recommendation, anomaly detection and so on,” he said.
The system is organized into pods, which are sets of resources designed to process the data in the Pinecone database. The company offers a single pod for free to help customers get comfortable with the product and perform a simple proof of concept. After that, they start paying based on the number of pods.
He is confident that the company has architected the system in such a way that it can scale to billions of objects. “You’re able to scale to as much as your software is able to actually withstand and you can actually orchestrate. We’ve designed the system such that there really isn’t any well-defined limit to how much data you can index and use,” he said.
As a serverless database, the customer doesn’t have to worry about provisioning at all, but they have to tell Pinecone just how much they are willing to spend each month, based on the amount of data they need to process.
“They kind of do the back of the envelope to figure out that x pods is going to be plenty for what we’re using in terms of the data that it can hold and the performance it would give me and that’s it.” After that the person simply signs up and with a few clicks in the console and an API call to create the index, it’s up and running and ready to use.
Liberty didn’t want to share growth numbers or employee numbers, but he says he expects to double the staff (whatever that means) in the next year. It’s worth noting that the startup had 10 employees at the time of the seed announcement.
In terms of diversity he said last year, ““We have instructed our recruiters to be proactive [in finding more diverse applicants], making sure they don’t miss out on great candidates, and that they bring us a diverse set of candidates.” In practice he says that has translated into 50% of new technical hires (as opposed to the total number of employees) have been female this year.
The company announced a $28 million Series A today led by Menlo Ventures with participation from new investor Tiger Global along with previous investors including Wing Venture Capital, who led the company’s seed funding. The company has now raised $38 million.
Tesla more than tripled its Austin gigafactory workforce in 2022
Tesla’s 2,500-acre manufacturing hub in Austin, Texas tripled its workforce last year, according to the company’s annual compliance report filed with county officials. Bloomberg first reported on the news.
The report filed with Travis County’s Economic Development Program shows that Tesla increased its Austin workforce from just 3,523 contingent and permanent employees in 2021 to 12,277 by the end of 2022. Bloomberg reports that just over half of Tesla’s workers reside in the county, with the average full-time employee earning a salary of at least $47,147. Outside of Tesla’s factory, the average salary of an Austin worker is $68,060, according to data from ZipRecruiter.
TechCrunch was unable to acquire a copy of the report, so it’s not clear if those workers are all full-time. If they are, Tesla has hired a far cry more full-time employees than it is contracted to do. According to the agreement between Tesla and Travis County, the company is obligated to create 5,001 new full-time jobs over the next four years.
The contract also states that Tesla must invest about $1.1 billion in the county over the next five years. Tesla’s compliance report shows that the automaker last year invested $5.81 billion in Gigafactory Texas, which officially launched a year ago at a “Cyber Rodeo” event. In January, Tesla notified regulators that it plans to invest another $770 million into an expansion of the factory to include a battery cell testing site and cathode and drive unit manufacturing site. With that investment will come more jobs.
Tesla’s choice to move its headquarters to Texas and build a gigafactory there has helped the state lead the nation in job growth. The automaker builds its Model Y crossover there and plans to build its Cybertruck in Texas, as well. Giga Texas will also be a model for sustainable manufacturing, CEO Elon Musk has said. Last year, Tesla completed the first phase of what will become “the largest rooftop solar installation in the world,” according to the report, per Bloomberg. Tesla has begun on the second phase of installation, but already there are reports of being able to see the rooftop from space. The goal is to generate 27 megawatts of power.
Musk has also promised to turn the site into an “ecological paradise,” complete with a boardwalk and a hiking/biking trail that will open to the public. There haven’t been many updates on that front, and locals have been concerned that the site is actually more of an environmental nightmare that has led to noise and water pollution. The site, located at the intersection of State Highway 130 and Harold Green Road, east of Austin, is along the Colorado River and could create a climate catastrophe if the river overflows.
The site of Tesla’s gigafactory has also historically been the home of low-income households and has a large population of Spanish-speaking residents. It’s not clear if the jobs at the factory reflect the demographic population of the community in which it resides.
Launch startup Stoke Space rolls out software tool for complex hardware development
Stoke Space, a company that’s developing a fully reusable rocket, has unveiled a new tool to let hardware companies track the design, testing and integration of parts. The new tool, Fusion, is targeting an unsexy but essential aspect of the hardware workflow.
It’s a solution born out of “ubiquitous pain in the industry,” Stoke CEO Andy Lapsa said in a recent interview. The current parts tracking status quo is marked by cumbersome, balkanized solutions built on piles of paperwork and spreadsheets. Many of the existing tools are not optimized “for boots on the ground,” but for finance or procurement teams, or even the C-suite, Lapsa explained.
In contrast, Fusion is designed to optimize simple inventory transactions and parts organization, and it will continue to track parts through their lifespan: as they are built into larger assemblies and go through testing. In an extreme example, such as hardware failures, Fusion will help teams connect anomalous data to the exact serial numbers of the parts involved.
“If you think about aerospace in general, there’s a need and a desire to be able to understand the part pedigree of every single part number and serial number that’s in an assembly,” Lapsa said. “So not only do you understand the configuration, you understand the history of all of those parts dating back to forever.”
While Lapsa clarified that Fusion is the result of an organic in-house need for better parts management – designing a fully reusable rocket is complicated, after all – turning it into a sell-able product was a decision that the Stoke team made early on. It’s a notable example of a rocket startup generating pathways for revenue while their vehicle is still under development.
Fusion offers particular relevance to startups. Many existing tools are designed for production runs – not the fast-moving research and development environment that many hardware startups find themselves, Lapsa added. In these environments, speed and accuracy are paramount.
Brent Bradbury, Stoke’s head of software, echoed these comments.
“The parts are changing, the people are changing, the processes are changing,” he said. “This lets us capture all that as it happens without a whole lot of extra work.”
Amid a boom in AI accelerators, a UC Berkeley-focused outfit, House Fund, swings open its doors
Companies at the forefront of AI would naturally like to stay at the forefront, so it’s no surprise they want to stay close to smaller startups that are putting some of their newest advancements to work.
Last month, for example, Neo, a startup accelerator founded by Silicon Valley investor Ali Partovi, announced that OpenAI and Microsoft have offered to provide free software and advice to companies in a new track focused on artificial intelligence.
Now, another Bay Area outfit — House Fund, which invests in startups with ties to UC Berkeley — says it is launching an AI accelerator and that, similarly, OpenAI, Microsoft, Databricks, and Google’s Gradient Ventures are offering participating startups free and early access to tech from their companies, along with mentorship from top AI founders and executives at these companies.
We talked with House Fund founder Jeremy Fiance over the weekend to get a bit more color about the program, which will replace a broader-based accelerator program House Fund has run and whose alums include an additive manufacturing software company, Dyndrite, and the managed app development platform Chowbotics, whose most recent round in January brought the company’s total funding to more than $60 million.
For founders interested in learning more, the new AI accelerator program runs for two months, kicking off in early July and ending in early September. Six or so companies will be accepted, with the early application deadline coming up next week on April 13th. (The final application deadline is on June 1.) As for the time commitment involved across those two months, every startup could have a different experience, says Fiance. “We’re there when you need us, and we’re good at staying out of the way.”
There will be the requisite kickoff retreat to spark the program and founders to get to know one another. Candidates who are accepted will also have access to some of UC Berkeley’s renowned AI professors, including Michael Jordan, Ion Stoica, and Trevor Darrell. And they can opt into dinners and events in collaboration with these various constituents.
As for some of the financial dynamics, every startup that goes through the program will receive a $1 million investment on a $10 million post-money SAFE note. Importantly, too, as with the House Fund’s venture dollars, its AI accelerator is seeking startups that have at least one Berkeley-affiliated founder on the co-founding team. That includes alumni, faculty, PhDs, postdocs, staff, students, dropouts, and other affiliates.
There is no demo day. Instead, says Fiance, founders will receive “directed, personal introductions” to the VCs who best fit with their startups.
Given the buzz over AI, the new program could supercharge House Fund, the venture organization, which is already growing fast. Fiance launched it in 2016 with just $6 million and it now manages $300 million in assets, including on behalf of Berkeley Endowment Management Company and the University of California.
At the same time, the competition out there is fierce and growing more so by the day.
Though OpenAI has offered to partner with House Fund, for example, the San Francisco-based company announced its own accelerator back in November. Called Converge, the cohort was to be made up of 10 or so founders who received $1 million each and admission to five weeks of office hours, workshops and other events that ended and that received their funding from the OpenAI Startup Fund.
Y Combinator, the biggest accelerator in the world, is also oozing with AI startups right now, all of them part of a winter class that will be talking directly with investors this week via demo days that are taking place tomorrow, April 5th, and on Thursday.
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