CEO of writer.com May Habib attends the Harper’s Bazaar At Work Summit, in partnership with Porsche and One&Only One Za’abeel, at Raffles London at The OWO on November 21, 2023 in London, England.
Dave Benett | Getty Images
San Francisco-based AI startup Writer debuted a large artificial intelligence model on Wednesday to compete with enterprise offerings from OpenAI, Anthropic and others. But, unlike some of those competitors, it doesn’t need to spend as much to train its AI.
The company told CNBC it spent about $700,000 to train its latest model, including the data and GPUs, compared to the millions of dollars competing startups spend to build their own models. Its strategy has caught the attention of investors.
Writer is raising up to $200 million at a $1.9 billion valuation, according to a source familiar with the situation who spoke with CNBC. That’s nearly quadruple the company’s valuation last September, when it raised $100 million at a valuation of more than $500 million.
The company cuts costs using synthetic data, or data created by AI. It’s designed to mimic the real-world information that’s usually fed into models without compromising privacy and is becoming a more popular method for training.
A study by AI researchers revised in June found that if current AI development trends continue, tech companies will “fully exhaust” the publicly available training data between 2026 and 2032, writing that “human-generated public text data cannot sustain scaling beyond this decade.”
Amazon has used synthetic data in training Alexa, Meta has used it to fine-tune its Llama models and Microsoft-backed OpenAI is incorporating it into its models, according to job descriptions posted by the company. Some experts, however, have warned that synthetic data should be used cautiously, as it has the potential to degrade model performance and exacerbate existing biases.
Waseem Alshikh, Writer’s co-founder and CTO, told CNBC that Writer has been working on its synthetic data pipeline for years.
“There’s some confusion in the industry about the definition of ‘synthetic’ data,” Alshikh said. “To be clear, we don’t train our models on fake or hallucination data, and we don’t use a model to generate random data… We take real, factual data and convert it to synthetic data that is specifically structured in a clearer and cleaner way for model training.”
The company’s generative AI allows corporate clients to use its large language models (LLMs) to generate human-sounding text for anything from LinkedIn posts to job descriptions to mission statements, as well as data analysis and summarization. The company has more than 250 enterprise customers, including Accenture, Uber, Salesforce, L’Oreal and Vanguard, who use the tech across sectors like support, IT, operations, sales, and marketing.
The generative AI market is poised to top $1 trillion in revenue within a decade. To date in 2024, investors have pumped $26.8 billion into 498 generative AI deals, according to PitchBook, and companies in the sector raised $25.9 billion in 2023, up more than 200% from 2022.
Co-founder & CEO of Rippling Parker Conrad speaks onstage during the TechCrunch Disrupt conference in San Francisco on Oct. 20, 2022
Kimberly White | TechCrunc | Getty Images
Human resources software startup Rippling sued competitor Deel in federal district court on Monday, claiming that “Deel cultivated a spy” to orchestrate a trade-secret theft.
The employee met with Deel executives and passed internal Rippling records to a reporter, according to San Francisco-based Rippling’s complaint in the U.S. District Court for California’s Northern District.
Rippling claimed in the filing Deel violated the 1970 Racketeer Influenced and Corrupt Organizations Act and misappropriated trade secrets.
The two startups are among the most world’s most valuable. Investors valued Rippling at $13.5 billion in a funding round announced last year, while Deel told media outlets in 2023 that it was worth $12 billion. Deel ranked No. 28 on CNBC’s 2024 Disruptor 50 list.
“Weeks after Rippling is accused of violating sanctions law in Russia and seeding falsehoods about Deel, Rippling is trying to shift the narrative with these sensationalized claims,” a Deel spokesperson told CNBC in an email. “We deny all legal wrongdoing and look forward to asserting our counterclaims.”
Rippling confirmed its findings earlier this month. The company’s general counsel sent a letter to three Deel executives that referred to a new Slack channel, and the Deel spy quickly looked for it. Rippling subsequently served a court order to the spy at its office in Dublin, Ireland requiring him to preserve information on his mobile phone.
“Deel’s spy lied to the court-appointed solicitor about the location of his phone, and then locked himself in a bathroom — seemingly in order to delete evidence from his phone — all while the independent solicitor repeatedly warned him not to delete materials from his device and that his non-compliance was breaching a court order with penal endorsement,” Rippling said in Monday’s filing. “The spy responded: ‘I’m willing to take that risk.’ He then fled the premises.”
Rippling hired the person whom it calls the Deel spy for a management role in 2023, as the two companies were becoming more competitive, the filing says. Deel had used Rippling’s software, but Rippling opted to not renew Deel’s contract, according to the legal filing.
The spy repeatedly accessed information about Rippling customers, quotes, sales calls, demos and support requests in internal Slack repositories, according to the filing. He found and downloaded Rippling’s guidance on how to go up against Deel for prospective business, too, the filing says.
Then, in February, a reporter at The Information sent an inquiry to Rippling that included Slack messages from inside Rippling, which the startup concluded were collected by the Deel spy, the filing says. Additionally, email records suggest that the spy met with Deel executives in December, Rippling said in the complaint.
“We always prefer to win by building the best products and we don’t turn to the legal system lightly,” Parker Conrad, Rippling’s co-founder and CEO, said in a Monday X post. “But we are taking this extraordinary step to send a clear message that this type of misconduct has no place in our industry.”
This isn’t Conrad’s first legal entanglement over data access. In 2015, ADP dropped a defamation lawsuit that claimed his previous HR startup, Zenefits, had obtained information from clients in order to provide them with payment processing services.
Each year 36 million trees fall due to decay, disease, natural disasters or clearing for new development. The vast majority of those trees are either burned, sent to a landfill or ground up for mulch, which wastes energy and causes carbon emissions.
Now, new technology is being used to find, transport and recycle that wood and make it useful once again.
Cambium is a startup aiming to disrupt the wood recycling space. Its Baltimore-based researchers are working on new ways to track, treat and transfer old wood into the supply chain. It bills itself as the platform “where timber meets tech.”
“We make it really easy to source wood that would have otherwise been wasted and we build technology for the wood industry so that we can save material, create new local jobs and address climate change at scale,” said CEO Ben Christensen.
Every piece of Cambium’s “carbon smart” wood has a barcode. Scan it, and Cambium’s app will identify what the species is, when it was milled and what its grade is.
Cambium’s technology helps find, recycle and then deliver the wood across the United States and to parts of Canada. The company works with local tree care services, trucking companies and saw mills as well as companies like Amazon, CBRE, Gensler and Room and Board.
“We help truckers coordinate loads so they can actually move this material, and then we help sawmills source that material, track that material when they’re actually using it within their sawmill and then ultimately sell that material as well,” Christensen said.
Recycled wood at Cambium.
Van Applegate | CNBC
While there are local wood recyclers, no one else is addressing the supply chain on a national scale, said Christensen, adding that he expects to eventually go global. This potential is enticing to investors.
“For us, as a venture capitalist who is looking to invest in businesses that kind of can go to the moon and become billion dollar businesses, this meets all the criteria,” said Adrian Fenty, founding managing partner at MaC Venture Capital.
Cambium is also backed by Volo Earth Ventures, NEA and Revolution’s Rise of the Rest Seed Fund, among others. The startup has raised $28.5 million in total funding so far.
If it was possible to salvage all the discarded wood material in the U.S., humans could source about half of our total demand, Christensen said.
Cambium doubled its sales last year, and Christensen said the big growth was on the software side. Its revenue comes from direct sales of wood to end users and from sales of software into the wood industry to facilitate moving, tracking and selling the recycled product.
“It’s critical for Silicon Valley investors, because we don’t want to invest in a wood company,” Fenty said. “We don’t want to invest in a construction company. We want to invest in a software company.”
Among the challenges ahead are the Trump administration’s tariffs on Canadian lumber, Christensen said. Those tariffs are expected to impact Cambium’s business, especially in the northeast region of the U.S.
“We’re moving material to sawmills that are 10 or 20 miles away across the border, and so obviously trade policy really impacts how that material moves,” Christensen said.
CNBC producer Lisa Rizzolo contributed to this piece.
Google DeepMind co-founder and Chief Executive Officer Demis Hassabis speaks during the Mobile World Congress, the telecom industry’s biggest annual gathering, in Barcelona, Spain, Feb. 26, 2024.
Pau Barrena | Afp | Getty Images
LONDON — Artificial intelligence that can match humans at any task is still some way off — but it’s only a matter of time before it becomes a reality, according to the CEO of Google DeepMind.
Speaking at a briefing in DeepMind’s London offices on Monday, Demis Hassabis said that he thinks artificial general intelligence (AGI) — which is as smart or smarter than humans — will start to emerge in the next five or 10 years.
“I think today’s systems, they’re very passive, but there’s still a lot of things they can’t do. But I think over the next five to 10 years, a lot of those capabilities will start coming to the fore and we’ll start moving towards what we call artificial general intelligence,” Hassabis said.
Hassabis defined AGI as “a system that’s able to exhibit all the complicated capabilities that humans can.”
“We’re not quite there yet. These systems are very impressive at certain things. But there are other things they can’t do yet, and we’ve still got quite a lot of research work to go before that,” Hassabis said.
Hassabis isn’t alone in suggesting that it’ll take a while for AGI to appear. Last year, the CEO of Chinese tech giant Baidu Robin Li said he sees AGI is “more than 10 years away,” pushing back on excitable predictions from some of his peers about this breakthrough taking place in a much shorter timeframe.
Some time to go yet
Hassabis’ forecast pushes the timeline to reach AGI some way back compared to what his industry peers have been sketching out.
Dario Amodei, CEO of AI startup Anthropic, told CNBC at the World Economic Forum in Davos, Switzerland in January that he sees a form of AI that’s “better than almost all humans at almost all tasks” emerging in the “next two or three years.”
Other tech leaders see AGI arriving even sooner. Cisco’s Chief Product Officer Jeetu Patel thinks there’s a chance we could see an example of AGI emerge as soon as this year. “There’s three major phases” to AI, Patel told CNBC in an interview at the Mobile World Congress event in Barcelona earlier this month.
“There’s the basic AI that we’re all experience right now. Then there is artificial general intelligence, where the cognitive capabilities meet those of humans. Then there’s what they call superintelligence,” Patel said.
“I think you will see meaningful evidence of AGI being in play in 2025. We’re not talking about years away,” he added. “I think superintelligence is, at best, a few years out.”
Artificial super intelligence, or ASI, is expected to arrive after AGI and surpass human intelligence. However, “no one really knows” when such a breakthrough will happen, Hassabis said Monday.
Hassabis said that the main challenge with achieving artificial general intelligence is getting today’s AI systems to a point of understanding context from the real world.
While it’s been possible to develop systems that can break down problems and complete tasks autonomously in the realm of games — such as the complex strategy board game Go — bringing such a technology into the real world is proving harder.
“The question is, how fast can we generalize the planning ideas and agentic kind of behaviors, planning and reasoning, and then generalize that over to working in the real world, on top of things like world models — models that are able to understand the world around us,” Hassabis said.”
“And I think we’ve made good progress with the world models over the last couple of years,” he added. “So now the question is, what’s the best way to combine that with these planning algorithms?”
Hassabis and Thomas Kurian, CEO of Google’s cloud computing division, said that so-called “multi-agent” AI systems are a technological advancement that’s gaining a lot of traction behind the scenes.
Hassabis said lots of work is being done to get to this stage. One example he referred to is DeepMind’s work getting AI agents to figure out how to play the popular strategy game “Starcraft.”
“We’ve done a lot of work on that with things like Starcraft game in the past, where you have a society of agents, or a league of agents, and they could be competing, they could be cooperating,” DeepMind’s chief said.
“When you think about agent to agent communication, that’s what we’re also doing to allow an agent to express itself … What are your skills? What kind of tools do you use?” Kurian said.
“Those are all elements that you need to be able to ask an agent a question, and then once you have that interface, then other agents can communicate with it,” he added.