Cognigo, a startup that aims to use AI and machine learning to help enterprises protect their data and stay in compliance with regulations like GDPR, today announced that it has raised an $8.5 million Series A round. The round was led by Israel-based crowdfunding platform OurCrowd, with participation from privacy company Prosegur and State of Mind Ventures.The company promises that it can help businesses protect their critical data assets and prevent personally identifiable information from leaking outside of the company’s network. And it says it can do so without the kind of hands-on management that’s often required in setting these kinds of systems up and managing them over time. Indeed, Cognigo says that it can help businesses achieve GDPR compliance in days instead of months. To do this, the company tells me, it’s using pre-trained language models for data classification. That model has been trained to detect
This simple spreadsheet of machine learning foibles may not look like much but it’s a fascinating exploration of how machines “think.” The list, compiled by researcher Victoria Krakovna, describes various situations in which robots followed the spirit and the letter of the law at the same time.For example, in the video below a machine learning algorithm learned that it could rack up points not by taking part in a boat race but by flipping around in a circle to get points. In another simulation “where survival required energy but giving birth had no energy cost, one species evolved a sedentary lifestyle that consisted mostly of mating in order to produce new children which could be eaten (or used as mates to produce more edible children).” This led to what Krakovna called “indolent cannibals.” It’s obvious that these machines aren’t “thinking” in any real sense but
Today, Google Cloud announced Kubeflow pipelines and AI Hub, two tools designed to help data scientists put the models they create to work across their organizations.Rajen Sheth, director of product management for Google Cloud’s AI and ML products says that the company recognized that data scientists too often build models that never get used. He says that if machine learning is really a team sport, as Google believes, models must get passed from data scientists to data engineers and developers who can build applications based on them. To help fix that, Google is announcing Kubeflow pipelines, which are an extension of Kubeflow, an open source framework built on top of Kubernetes designed specifically for machine learning. Pipelines are essentially containerized building blocks that people in the machine learning ecosystem can string together to build and manage machine learning workflows. By placing the model in a container, data scientists can
Picture it: you have the perfect song for Kelly Clarkson. It’s a mix of genres and styles best described as “Since U Been Gone” meets “911 Is A Joke.” How do you get it in front of Kelly so she can add it to her next album (imagine her singing “My heart is on fire when you’re not there/But the Austin fire department doesn’t care”)? You talk to MyPart.MyPart lets aspiring creators and musicians submit stuff to their favorite artists. A vetting system separates the hits from the chaff and, by ensuring the artist doesn’t see unsolicited content, reduces lawsuits. MyPart, founded in 2016, has added a number of interesting features to its platform thanks to AI and machine learning. “MyPart has recently finalized our seed round with $1M, and were named a MassChallenge 2018 top 10 startup award finalist,” said co-founder Matan Kollnescher. “This followed a $150k
Last summer, Google introduced its own take on Bitmoji with the launch of “Mini” stickers in its keyboard app, Gboard, which leverage machine learning to create illustrated stickers based on your selfie. Today, Google is expanding the Mini Stickers with the launch of what it calls “Emoji Minis” – meaning, emoji-sized stickers that look like you.Similar to the initial launch of Mini stickers, the new emoji are also created using machine learning techniques, Google says. The company said the idea is to give people a way to use emoji they feel better represent who they really are. “Emoji Minis are designed for those who may have stared into the eyes of emoji and not seen yourself staring back,” explained Google, in a blog post. “These sticker versions of the emoji you use every day are customizable so you can make them look just like you.” That means your
Facebook announced today that it has removed 8.7 million pieces of content last quarter that violated its rules against child exploitation, thanks to new technology. The new AI and machine learning tech, which was developed and implemented over the past year by the company, removed 99 percent of those posts before anyone reported them, said Antigone Davis, Facebook’s global head of safety, in a blog post.The new technology examines posts for child nudity and other exploitative content when they are uploaded and, if necessary, photos and accounts are reported to the National Center for Missing and Exploited Children. Facebook had already been using photo-matching technology to compare newly uploaded photos with known images of child exploitation and revenge porn, but the new tools are meant to prevent previously unidentified content from being disseminated through its platform. The technology isn’t perfect, with many parents complaining that innocuous photos of
The Israeli cybersecurity venture studio Team8 has raised $85 million in new financing from a clutch of new and returning strategic investors including Walmart, Airbus, SoftBank, and Microsoft’s investment arm, M-12.The studio’s plans to raise a larger fund were first reported by PEHub in May. Team8 has long believed that by combining the strengths and security interests of strategic corporate partners it could develop better cybersecurity solutions (or companies) that would be attractive to its investors and clients. Indeed, that was the thesis behind the $23 million that Team8 raised in 2016 when it was still proving out the model.
The company’s previous rounds of funding managed to bring Cisco Investments, Bessemer Venture Partners, Innovation Endeavors and Alcatel-Lucent into the fold. Now banks like Scotiabank and Barclays, ratings agencies like Moody’s, and insurers
In its first institutional funding round, Oh My Green has raised $20 million from Initialized Capital, Powerplant Ventures, Backed VC, ZhenFund, Talis Capital and the Stanford StartX Fund to bring healthier foods to offices around the U.S.The concierge-style startup, which completed Y Combinator’s startup accelerator in 2016, provides businesses in San Francisco, Los Angeles, Seattle, Chicago, Austin, Denver, Boston, New York City and Nashville nutritional snacks and meals. It stocks office snack pantries — a staple at tech startups — caters events, manages cafes and provides wellness programming. Its goal is to be a one-stop shop for corporate nutritional wellness. The San Francisco-based company was founded in 2014 by Michael Heinrich. Based off my conversation with him earlier this week, I’m guessing he wouldn’t approve of the TechCrunch snack cupboard, which includes a year-long supply of Skittles, M&Ms and Fruit by the Foot. “I wanted to do
Paperspace wants to help developers build artificial intelligence and machine learning applications with a software/hardware development platform powered by GPus and other powerful chips. Today, the Winter 2015 Y Combinator grads announced a $13 million Series A.Battery Ventures led the round with participation from SineWave Ventures, Intel Capital and Sorenson Ventures. Existing investor Initialized Capital also participated. Today’s investment brings the total amount to $19 million raised. Dharmesh Thakker, a general partner with Battery Ventures sees Paperspace as being in the right place at the time. As AI and machine learning take off, developers need a set of tools and GPU-fueled hardware to process it all. “Major silicon, systems and Web-scale computing providers need a cloud-based solution and software ‘glue’ to make deep learning truly consumable by data-driven organizations, and Paperspace is helping to provide that,” Thakker said in a statement. Paperspace provides its own GPU-powered servers to help
In today’s world of Slack, email and a gazillion other web apps and services, it’s become increasingly hard to search for information. Did your boss Slack you or email you that information about your bonus? Or did they share it via a Google Doc? Who knows? Clearly not you, but Journal knows.Journal, a machine learning and natural language processing-powered platform designed to search across all your web services and tools, today announced a $1.5 million seed round led by Social Capital. Since receiving the funding about a year ago, Journal has been able to launch a beta community of users. Today, Journal is publicly launching its Mac app, web app and Chrome extension. “We’re passionate about helping people use information effectively,” Journal co-founder and CEO Samiur Rahman told TechCrunch. “In this case, we want to help people manage their knowledge. So we want to help individuals to leverage
Celonis has been helping companies analyze and improve their internal processes using machine learning. Today the company announced it was providing that same solution as a cloud service with a few nifty improvements you won’t find on prem.The new approach, called Celonis Intelligent Business Cloud, allows customers to analyze a workflow, find inefficiencies and offer improvements very quickly. Companies typically follow a workflow that has developed over time and very rarely think about why it developed the way it did, or how to fix it. If they do, it usually involves bringing in consultants to help. Celonis puts software and machine learning to bear on the problem. Co-founder and CEO Alexander Rinke says that his company deals with massive volumes of data and moving all of that to the cloud makes sense. “With Intelligent Business Cloud, we will unlock that [on prem data], bring it to the cloud in
TechCrunch: Hey Portal, dial MarkPortal: Do you mean Mark Zuckerberg? TC: Yes Portal: Dialling Mark…
TC: Hi Mark! Nice choice of grey t-shirt. MZ: Uh, new phone who dis? — oh, hi, er, TechCrunch… TC: Thanks for agreeing to this entirely fictional interview, Mark! MZ: Sure — anytime. But you don’t mind if I tape over the camera do you? You see I’m a bit concerned about my privacy here at, like, home TC: We feel you, go ahead. As you can see, we already took the precaution of wearing this large rubber face mask of, well, of yourself Mark. And covering the contents of our bedroom with these paint-splattered decorator sheets. MZ: Yeah, I saw that. It’s a bit creepy tbh TC: Go on and get all taped up. We’ll wait. [sound of Mark calling Priscilla to bring the tape dispenser] [Portal’s camera jumps out to assimilate
If you’re considering making the jump to Google’s newly announced Pixel 3 and Pixel 3 XL, you’re in the right place. Whether you’re a Pixel 2 owner eyeing greener pastures or a bargain type hunting for a last-gen smartphone that’s still top of the line, comparing new and old is often useful.On specs alone, the Pixel 3 shares most of its DNA with the Pixel 2, but there are a handful of meaningful differences and they’re not all obvious. What is obvious: The Pixel 3’s AMOLED screen is now 5.5 inches compared to the Pixel 2’s 5 inch display. The Pixel 3 XL now offers a 6.3 inch display, up .3 inches from the Pixel 2 XL. The Pixel 3 and Pixel 3 XL upgrade the Pixel 2’s processor slightly and add an additional front-facing camera for some of the device’s newest tricks. The primary camera
Google’s Pixel 2 introduced one of the best smartphone cameras ever made and the Pixel 3 brings even more more bells and whistles sure to please mobile photographers. On paper, the Pixel 3’s camera doesn’t look much different than its recent forebear. But, because we’re talking about Google, software is where the device will really shine. We’ll go over everything that’s new.
Starting with specs, both the Pixel 3 and the Pixel 3 XL will sport a 12.2MP rear camera with an f/1.8 aperture and an 8MP dual front camera capable of both normal field of view and ultra-wide angle shots. The rear video camera captures 1080p video at 30, 60 or 120 fps, while the front-facing video camera is capable of capturing 1080p video at 30fps. Google did not add a second rear-facing camera, deeming it
At a special event in New York City, Google announced some of its latest, flagship hardware devices. During the hour-long press conference Google executives and product managers took the wraps off the company’s latest products and explained their features. Chief among the lot is the Pixel 3, Google’s latest flagship Android device. Like the Pixel 2 before it, the Pixel 3’s main feature is its stellar camera but there’s a lot more magic packed inside the svelte frame.Android flagship (spotted by 9 to 5 Google) does boast a sizable notch up top, in keeping with earlier images of the larger XL. Makes sense, after all, Google went out of its way to boast about notch functionality when it introduced Pie, the latest version of its mobile OS. The device is available for preorder today and will start
It’s been less than six months since Adobe acquired commerce platform Magento for $1.68 billion and today, at Magento’s annual conference, the company announced the first set of integrations that bring the analytics and personalization features of Adobe’s Experience Cloud to Magento’s Commerce Cloud.In many ways, the acquisition of Magento helps Adobe close the loop in its marketing story by giving its customers a full spectrum of services that go from analytics, marketing and customer acquisition all the way to closing the transaction. It’s no surprise then that the Experience Cloud and Commerce Cloud are growing closer to, in Adobe’s words, “make every experience shoppable.” “From the time that this company started to today, our focus has been pretty much exactly the same,” Adobe’s SVP of Strategic Marketing Aseem Chandra told me. “This is, how do we deliver better experiences across any channel in which our customers
Last year 30 leading venture investors told us about a fundamental shift from early stage North American VR investment to later stage Chinese computer vision/AR investment — but they didn’t anticipate its ferocity.
Digi-Capital’s AR/VR/XR Analytics Platform showed Chinese investments into computer vision and augmented reality technologies surging to $3.9 billion in the last 12 months, while North American augmented and virtual reality investment fell from nearly $1.5 billion in the fourth quarter of 2017 to less than $120 million in the third quarter of 2018. At the same time, VC sentiment on virtual reality softened significantly.
What a difference a year makes.
Dealflow (dollars)What VCs said a year ago
When we spoke to venture capitalists