Category: natural language processing

With more cash and a launch, Vannevar Labs is reconnecting Silicon Valley to its defense industry roots



Silicon Valley was once one of the most productive regions in the country for the defense industry, churning out chips and technologies that helped the United States overtake the Soviet Union during the Cold War. Since then, the region has been known far less for silicon and defense than for the consumer internet products of Google, Facebook and Netflix.

A small number of startups though are attempting to revitalize that important government-industry nexus as the rise of China pushes more defense planners in Washington to double down on America’s technical edge. Vannevar Labs is one of this new crop, and it has hit some new milestones in its quest to displace traditional defense contractors with Silicon Valley entrepreneurial acumen.

I last chatted with the company just as it was debuting in late 2019, having raised a $4.5 million seed. The company has been quiet and heads down the past two years as it developed a product and traction within the defense establishment. Now it’s ready to reveal a bit more of what all that work has culminated in.

First, the company officially launched its Vannevar Decrypt product in January of this year. It’s focused on foreign language natural language processing, organizing overseas data and resources that are collected by the intelligence community and then immediately translating and interpreting those documents for foreign policy decision-makers. CEO and co-founder Brett Granberg said that the product “went (Read more...)

Google’s Gradient Ventures leads $8.2M Series A for Vault Platform’s misconduct reporting SaaS



Fixing workplace misconduct reporting is a mission that’s snagged London-based Vault Platform backing from Google’s AI focused fund, Gradient Ventures, which is the lead investor in an $8.2 million Series A that’s being announced today.

Other investors joining the round are Illuminate Financial, along with existing investors including Kindred Capital and Angular Ventures. Its $4.2M seed round was closed back in 2019.

Vault sells a suite of SaaS tools to enterprise-sized or large/scale-up companies to support them to pro-actively manage internal ethics and integrity issues. As well as tools for staff to report issues, data and analytics is baked into the platform — so it can support with customers’ wider audit and compliance requirements.

In an interview with TechCrunch, co-founder and CEO Neta Meidav said that as well as being wholly on board with the overarching mission to upgrade legacy reporting tools like hotlines provided to staff to try to surface conduct-related workplace risks (be that bullying and harassment; racism and sexism; or bribery, corruption and fraud), as you might expect Gradient Ventures was interested in the potential for applying AI to further enhance Vault’s SaaS-based reporting tool.

A feature of its current platform, called ‘GoTogether’, consists of an escrow system that allows users to submit misconduct reports to the relevant internal bodies but only if they are not the first or only person to have made a report about the same person — the idea being that can help encourage staff (or outsiders, where open reporting is enabled) (Read more...)

StudySmarter books $15M for a global ‘personalized learning’ push



More money for the edtech boom: Munich-based StudySmarter, which makes digital tools to help learners of all ages swat up — styling itself as a ‘lifelong learning platform’ — has closed a $15 million Series A.

The round is led by sector-focused VC fund, Owl Ventures. New York-based Left Lane Capital is co-investing, along with Lars Fjeldsoe-Nielsen (ex WhatsApp, Uber and Dropbox; now GP at Balderton Capital), and existing early stage investor Dieter von Holtzbrinck Ventures (aka DvH Ventures).

The platform, which launched back in 2018 and has amassed a user-base of 1.5M+ learners — with a 50/50 split between higher education students and K12 learners, and with main markets so far in German speaking DACH countries in Europe — uses AI technologies like natural language processing (NLP) to automate the creation of text-based interactive custom courses and track learners’ progress (including by creating a personalized study plan that adjusts as they go along).

StudySmarter claims its data shows that 94% of learners achieve better grades as a result of using its platform.

While NLP is generally most advanced for the English language, the startup says it’s confident its NLP models can be transferred to new languages without requiring new training data — claiming its tech is “scalable in any language”. (Although it concedes its algorithms increase in accuracy for a given language as users upload more content so the software itself is undertaking a learning journey and will necessarily be at a different point on the learning curve (Read more...)

Hugging Face raises $40 million for its natural language processing library



Hugging Face has raised a $40 million Series B funding round — Addition is leading the round. The company has been building an open source library for natural language processing (NLP) technologies. You can find the Transformers library on GitHub — it has 42,000 stars and 10,000 forks.

Existing investors Lux Capital, A.Capital and Betaworks also participated in today’s funding round. Other investors include Dev Ittycheria, Olivier Pomel, Alex Wang, Aghi Marietti, Florian Douetteau, Richard Socher, Paul St. John, Kevin Durant and Rich Kleiman.

With Transformers, you can leverage popular NLP models, such as BERT, GPT, XLNet, T5 or DistilBERT and use those models to manipulate text in one way or another. For instance, you can classify text, extract information, automatically answer questions, summarize text, generate text, etc.

There are many different use cases for NLP. A popular one has been support chatbot. For instance, challenger bank Monzo has been using Hugging Face behind the scenes to answer questions from its customers. Overall, around 5,000 companies are using Hugging Face in one way or another, including Microsoft with its search engine Bing.

When it comes to business model, the startup has recently launched a way to get prioritized support, manage private models and host the inference API for you. Clients include Bloomberg, Typeform and Grammarly.

With the new funding round, the company plans to triple its headcount in New York and Paris — there will be remote positions too. Interestingly, the company is also sharing some details about its bank (Read more...)

With AI translation service that rivals professionals, Lengoo attracts new $20M round



Most people who use AI-powered translation tools do so for commonplace, relatively unimportant tasks like understanding a single phrase or quote. Those basic services won’t do for an enterprise offering technical documents in 15 languages — but Lengoo’s custom machine translation models might just do the trick. And with a new $20 million B round, they may be able to build a considerable lead.

The translation business is a big one, in the billions, and isn’t going anywhere. It’s simply too common a task to need to release a document, piece of software or live website in multiple languages — perhaps dozens.

These days that work is done by translation agencies, which employ expert speakers to provide translation on demand at a high level of quality. The rise of machine translation as an everyday tool hasn’t affected them as much as you might think, since the occasional Portuguese user using Google’s built-in webpage translation on a Korean website is very much a niche case, and things like translating social media posts or individual sentences isn’t really something you could or would farm out to professionals.

In these familiar cases, “good enough” is the rule, since the bare meaning is all anyone really wants or needs. But if you’re releasing a product in 10 different markets speaking 10 different languages, it won’t do to have the instructions, warnings, legal agreements or technical documentation perfect in one language and merely fine in the other nine.