CrowdFlower: Powering the Human Side of Artificial Intelligence
CrowdFlower is solving machine learning's dirty secret – that humans are still needed to train the models we all rely on every day.
CrowdFlower is solving machine learning's dirty secret – that humans are still needed to train the models we all rely on every day.
Effectively harnessing data analytics and machine learning allow campaigns and companies to improve the ROI of marketing costs and to gain deeper insight into consumer data to make better business decisions.
Nvidia has benefited from the crypto-mining boom, but has set itself up for continued success beyond blockchain.
It takes over $2.5B and 10 years to produce one drug. Artificial Intelligence has the power to halve each of that. Enter, BenevolentAI.
London-based virtual fitting room company Metail provides AR try-before-you-buy solutions and sets out to become the Google of sizing and shape
How Facebook is Leveraging Data and Machine Learning to Protect the Lives of its Users
DarkTrace is a UK-based start-up that is improving cyber-security through the use of machine learning and artificial intelligence to develop an ‘Enterprise Immune System’
In 2010, roughly 8.3% of US consumers, or 19 million people, were considered ‘unscorable’ by FICO, a credit rating service whose models serve as a key underpinning of the US system for assessing credit worthiness.[1] Included in this contingent of unscorable consumers are those lacking a credit history, read: millennials, who represent an untapped market opportunity for lenders. Also excluded from FICO are the underbanked, those who lack bank accounts and primarily transact in cash. Not only are the underbanked denied access to loans based on typical FICO filters, but they must resort to predatory alternatives, such as payday loans, whose prohibitively high interest rates trap them in a vicious cycle of deep indebtedness that is difficult to dig out of. Has the FICO score become an obsolete filter? And can a lender step in to provide loans to these underserved segments where traditional banks have neglected to do so – and profitably?
PredPol, crime prediction service
AlphaGo program shocked the world by defeating Lee Sedol, the world champion in Go. This post talks about how Google used data and algorithms to achieve this and how a seemingly recreational program will create and capture value for Google