Activeloop raises $11 million to give businesses a better way to leverage multimodal data for AI

Join We In Atlanta on April 10th And explore THE landscape of security Workforce. We will explore THE vision, benefits, And to use case of AI For security teams. Request A invite here.

Based in California Active loop, A to start up offer A dedicated database has streamline AI projects, Today announcement he has raised $11 million In series A funding Since Simplified Companies, Yes Combinator, Samsung Following (THE to start up acceleration arm of THE Samsung Band) And several other investors.

While there are several data platforms out there, Active loop, based by Princeton give up Davit Buniatyan, has carved A niche For himself with A system has tackle A of THE the biggest challenges companies confront Today: benefit unstructured multimodal data For training AI models. THE business complaints This technology, double "Deep Lake," allow teams has create AI apps has A cost up has 75% lower that walk offerings while increasing engineering teams productivity by up has quintuple.

THE work East important as more And more companies look For manners has faucet their complex datasets For AI apps target has different to use case. According to has McKinsey research, generative AI has THE potential has generate $2.6 thousand billion has $4.4 thousand billion In global business profits annually with significant impact through dozens of areas, including provide support interaction with clients, generator creative content For marketing And sales And writing software coded base on natural language prompts.

What do Active loop Deep Lake help with?

Today, training very efficient foundation AI models implied transaction with on petabyte scale unstructured data covering terms and conditions such as text, audio And video. THE stain generally requires teams has identify relevant datasets Since disorganized silos And put them has work on A in progress base with different storage And recovery technologies — something that requires A plot of master key coding And the integration Since engineers And can increase THE cost of THE project.

V.B. Event

THE AI Impact Tour – Atlanta

Continue OUR tour, were headed has Atlanta For THE AI Impact Tour stop on April 10th. This exclusive, invite only event, In Partnership with Microsoft, will functionality discussions on how generative AI East transform THE security Workforce. Space East limit, SO request A invite today.

Request A invite

Active loop targets This inconsistent approach with THE standardization of Deep Lake, which stores complex data — such as pictures, videos, And annotations, among others — In THE form of machine learning (ML)-native mathematical representations (tensors) And ease THE streaming of these tensors has SQL type Tensor Request Language, A in the browser visualization engine, Or deep learning executives as PyTorch And TensorFlow.

This given developers A platform For All, Since filtration And research multimodal data has follow up And comparing It is variants on time And streaming he For training models aiming has different to use case.

Activeloop raises $11 million to give businesses a better way to leverage multimodal data for AI

Join We In Atlanta on April 10th And explore THE landscape of security Workforce. We will explore THE vision, benefits, And to use case of AI For security teams. Request A invite here.

Based in California Active loop, A to start up offer A dedicated database has streamline AI projects, Today announcement he has raised $11 million In series A funding Since Simplified Companies, Yes Combinator, Samsung Following (THE to start up acceleration arm of THE Samsung Band) And several other investors.

While there are several data platforms out there, Active loop, based by Princeton give up Davit Buniatyan, has carved A niche For himself with A system has tackle A of THE the biggest challenges companies confront Today: benefit unstructured multimodal data For training AI models. THE business complaints This technology, double "Deep Lake," allow teams has create AI apps has A cost up has 75% lower that walk offerings while increasing engineering teams productivity by up has quintuple.

THE work East important as more And more companies look For manners has faucet their complex datasets For AI apps target has different to use case. According to has McKinsey research, generative AI has THE potential has generate $2.6 thousand billion has $4.4 thousand billion In global business profits annually with significant impact through dozens of areas, including provide support interaction with clients, generator creative content For marketing And sales And writing software coded base on natural language prompts.

What do Active loop Deep Lake help with?

Today, training very efficient foundation AI models implied transaction with on petabyte scale unstructured data covering terms and conditions such as text, audio And video. THE stain generally requires teams has identify relevant datasets Since disorganized silos And put them has work on A in progress base with different storage And recovery technologies — something that requires A plot of master key coding And the integration Since engineers And can increase THE cost of THE project.

V.B. Event

THE AI Impact Tour – Atlanta

Continue OUR tour, were headed has Atlanta For THE AI Impact Tour stop on April 10th. This exclusive, invite only event, In Partnership with Microsoft, will functionality discussions on how generative AI East transform THE security Workforce. Space East limit, SO request A invite today.

Request A invite

Active loop targets This inconsistent approach with THE standardization of Deep Lake, which stores complex data — such as pictures, videos, And annotations, among others — In THE form of machine learning (ML)-native mathematical representations (tensors) And ease THE streaming of these tensors has SQL type Tensor Request Language, A in the browser visualization engine, Or deep learning executives as PyTorch And TensorFlow.

This given developers A platform For All, Since filtration And research multimodal data has follow up And comparing It is variants on time And streaming he For training models aiming has different to use case.

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