Founded in 2007, Cortica has taken in total of funding of $69.4 million total funding to develop "the world's only unsupervised learning system capable of human level image understanding." Founded in 2012, Fortscale has taken in $39 million in total funding to develop User & Entity Behavioral Analytics (UEBA) which identifies "internal threats" to your business using machine learning algorithms. With $22 million in funding from investors that include Qualcomm and Cisco, Prospera has developed computer vision technologies that continuously monitor and analyze plant health, development and stress. We've recently written about more than 20 medical imaging startups, and one of those articles about "9 Artificial Intelligence Startups in Medical Imaging" featured Zebra Medical Vision which has taken in $20 million in funding so far and claims to have accumulated "one of the largest anonymized databases of medical imaging and clinical data available."
Today they announced the merging of their respective firms, Grit Labs and Pitch, to launch an institutional seed fund focused on AI and robotics. Last year, Coyne founded Pitch, a firm that helps early stage startups with fundraising, branding, marketing, PR, and launch logistics. The two will focus future investments on B2B robotics. So Grit Labs would invest between $1 million and $2 million total in each of its portfolio companies.
They're doing this with Mya, an intelligent chatbot that, much like a recruiter, interviews and evaluates job candidates. Since AI is dependent on a training set generated by a human team, it can promote bias rather than eliminating it, she adds. Grayevsky explains that Mya Systems "sets controls" over the kinds of data Mya uses to learn. This is why it's a possibility that rather than eliminating biases, AI HR tools might perpetuate them.
Insurtechs with expertise in robotics, artificial intelligence, IoT, blockchain and advanced analytics are encouraging insurance companies to rethink product development through collaboration. The report, "Global insurance market opportunities: Reimagining risk management," argues insurtech startups will likely play the role of enabler for insurance innovation rather than disrupt long-standing business models. "The insurance industry has been relatively slow to embrace digital technology compared with other industries. That reticence has opened a window of opportunity for entrepreneurs to deploy digital technology to improve the customer experience through a host of startup companies," Aon says.
The brainchild of Ludovic Huraux, a French entrepreneur best known for building a popular French dating site, Attractive World, Shapr is an app that helps you meet new professional connections. Every day Shapr pairs each of its users with 15 new connections, selected via algorithm through matching interests or career success. Shapr adapted its algorithm to include interests (both personal and professional) as added by a user, and career level as determined by a combination of human moderators and a machine learning algorithm. Though many networking groups, such as Meetup, have succeeded by siloing users by interest, Huraux believes deeply that connecting with people outside of your normal interest groups is the key to professional success.
The Engine initially raised $150 million for its first fund, but later tacked on the additional $50 million. MIT launched The Engine almost a year ago to provide resources to startups whose technologies might get stranded in the research lab because they would take more time and money to develop than most venture capitalists are willing to invest--think biotech, medical devices, robotics, advanced manufacturing, materials science, and energy. The Engine combines a venture fund and access to work space, expert advisors, educational workshops and events, and business services. The companies' founders include MIT professors Bob Langer, a prolific life sciences inventor, and Yet-Ming Chiang, a materials science and engineering expert who previously helped start A123 Systems, American Superconductor, and Desktop Metal.
Intel CEO Brian Krzanich said in an op-ed Monday that the company has invested more than $1 billion in business that are advancing the field of artificial intelligence. The investments have come through the Intel Capital investment fund and include financing for a number of AI startups, including Data Robot, Mighty AI, and Lumiata. Intel is making strategic investments spanning technology, R&D and partnerships with business, government, academia and community groups. That deal closed last month and Intel is already working on a fleet of level 4 autonomous vehicles using Mobileye's computer vision, sensor fusion, mapping, machine learning, and AI technology.
The venture arm of Salesforce.com is launching a $50 million fund to invest in startups employing artificial intelligence, the cloud computing firm told Reuters on Tuesday. "There's a tremendous surge in companies who are providing unique AI innovations," said John Somorjai, executive vice president of Salesforce Ventures. Venture capital investment in AI startups is rising quickly. For 2017, global financing for AI startups is projected to surpass $10.8 billion - nearly double the $5.6 billion spent in 2016, according to research firm CB Insights.
Between 1962 and 1970, the Beatles recorded nearly all their singles and albums at London's Abbey Road Studios using one of EMI's innovative REDD mixing consoles. "We are aware of the studio's heritage of continually tracking technology as it changed over the years," says Jon Eades, innovation manager at Abbey Road Red, the studio's technology incubator, which launched in 2015. Uberchord, an AI-powered guitar-learning app, now has licensing deals with Sony and Universal, including a collection of Beatles songs; another graduate, Tokyo-based QRATES, is the first online crowdfunding platform for artists and labels to collect pre-orders from fans to fund vinyl pressing. Abbey Road Red's latest intake includes AI Music, which has created an app called Ripple that personalises tracks for each listener.
The startup also provides engineered wood factories with software that uses machine learning to optimize how their adhesive is used in the production process. For example, right now there's a standard formula for creating engineered wood – you take wood chips, add adhesive, and press them together until they are bonded into the shape you want. On the other hand, others may use legacy adhesive solutions like urea-formaldehyde, but use Materialize.X's machine learning algorithms to optimize their manufacturing process. And the machine learning optimization can be useful in other manufacturing processes unrelated to engineered wood – right now the startup is testing algorithms to improve production in the steel industry.