Why vector databases are having a moment as the AI hype cycle peaks GenAI spurs demand for vector search startups, but database giants are also taking noteVector databases are all the rage, judging by the number of startups entering the space and the investors ponying up for a piece of the pie.
“Working with visual search and robotics at Amazon was when I really looked at vector search — I was thinking about new ways to do product discovery, and that very quickly converged on vector search,” Clark told TechCrunch.
“I think the same is likely to happen with vector databases,” Zaitsev told TechCrunch.
“Our pitch is, ‘we do advanced vector search in the best way possible.’ It is all about specialization.
At some point, users will face limitations if vector search is a critical component of your solution.”
Allison Cohen is the senior applied AI projects manager at Mila, a Quebec-based community of more than 1,200 researchers specializing in AI and machine learning.
One of the projects I managed involved building a dataset containing instances of subtle and overt expressions of bias against women.
I learned firsthand why this process is fundamental to building responsible applications, and also why it’s not done enough — it’s hard work!
What advice would you give to women seeking to enter the AI field?
How can investors better push for responsible AI?
For Informatica investors, it was the opposite: The price was too low to warrant selling — they wanted more, more, more — and their stock also dropped, down a similar amount over the same period.
The biggest by far of that bunch was the $28 billion deal to buy Slack at the end of 2020.
Informatica is also far smaller than Salesforce, making its potential revenue bump to Marc Benioff’s company modest.
The ace up Informatica’s sleeve is that while its total revenue growth is slow, one important segment of its revenues is expanding quickly.
If we were to compare Informatica cloud net-new ARR that it expects this year instead, the percentage becomes even smaller.
That’s privacy by design.”The funding is notable in part because Cape appeal to users is not yet proven.
The latest round is being co-led by A* and Andreessen Horowitz, with XYZ Ventures, ex/ante, Costanoa Ventures, Point72 Ventures, Forward Deployed VC, and Karman Ventures also participating.
Those jobs may exposed him to users (government departments) who treated the security of personal information and privacy around data usage as essential.
(Cape today also announced a partnership with USCellular — which itself provides a MNVO covering 12 cellular networks, and Doyle said that it’s talking with other telcos, too).
Although payments for this might be anonymous, a user’s data is still routed through the network infrastructure of the underlying carrier, making a users movements and usage observable.
Hackers are threatening to publish a huge stolen sanctions and financial crimes watchlist The stolen World-Check database contains 5.3 million recordsA financially motivated hacking group says it has stolen a confidential database containing millions of records that companies use for screening potential customers for links to sanctions and financial crime.
The hackers, which call themselves GhostR, said they stole 5.3 million records from the World-Check screening database in March and are threatening to publish the data online.
A portion of the stolen data, which the hackers shared with TechCrunch, includes individuals who were sanctioned as recently as this year.
The incident involves a third party’s data set, which includes a copy of the World-Check data file.
Banking giant HSBC shut down bank accounts belonging to several prominent British Muslims after the World-Check database branded them with “terrorism” tags.
Meta has released the latest entry in its Llama series of open source generative AI models: Llama 3.
Meta describes the new models — Llama 3 8B, which contains 8 billion parameters, and Llama 3 70B, which contains 70 billion parameters — as a “major leap” compared to the previous-gen Llama models, Llama 2 8B and Llama 2 70B, performance-wise.
In fact, Meta says that, for their respective parameter counts, Llama 3 8B and Llama 3 70B — trained on two custom-built 24,000 GPU clusters — are are among the best-performing generative AI models available today.
So what about toxicity and bias, two other common problems with generative AI models (including Llama 2)?
The company’s also releasing a new tool, Code Shield, designed to detect code from generative AI models that might introduce security vulnerabilities.
If you want to get your product in a grocery store in Mexico City, Dataplor has global location intelligence to help you do that.
The company raised $2 million in 2019 to bring Latin American food delivery vendors online.
Dataplor uses artificial intelligence, machine learning, large language models and a purpose-built technology platform to take in public domain data.
While that is not totally unique — there are companies like ThoughSpot, Esri and Near doing something similar around business and location intelligence — Dataplor’s “secret sauce” is combining all of that technology and public domain data with a human factor.
The round also includes participation from Quest Venture Partners, Acronym Venture Capital, Circadian Ventures, Two Lanterns Venture Partners and APA Venture Partners.
Building owners are often in the dark about their carbon pollution.
A new algorithm could shed light on itStarting this year, thousands of buildings in New York City will have to start reducing their carbon emissions.
There are plenty of tools out there that can convert an electric bill into estimated carbon emissions, but many are based on rough estimates.
It’s why Nzero, a carbon-tracking startup, developed a new algorithm, giving building owners reports that estimate carbon pollution down to the hour.
From there, the company’s software helps building owners identify upgrades and retrofits that will reduce emissions while also being the most cost effective.
The European Data Protection Board (EDPB) has published new guidance which has major implications for adtech giants like Meta and other large platforms.
The guidance, which was confirmed incoming Wednesday as we reported earlier, will steer how privacy regulators interpret the bloc’s General Data Protection Regulation (GDPR) in a critical area.
The full opinion of the EDPB on so-called “consent or pay” runs to 42-pages.
However a market leader imposing that kind of binary choice looks unviable, per the EDPB, an expert body made up of representatives of data protection authorities from around the EU.
“Online platforms should give users a real choice when employing ‘consent or pay’ models,” Talu wrote.
NeuBird founders Goutham Rao and Vinod Jayaraman came from PortWorx, a cloud native storage solution they eventually sold to PureStorage in 2019 for $370 million.
When they went looking for their next startup challenge last year, they saw an opportunity to combine their cloud native knowledge, especially around IT operations, with the burgeoning area of generative AI.
Rao, the CEO, says that while the cloud native community has done a good job at solving a lot of difficult problems, it has created increasing levels of complexity along the way.
“We’ve done an incredible job as a community over the past 10 plus years building cloud native architectures with service oriented designs.
At the same time, large language models were beginning to mature, so the founders decided to put them to work on the problem.
