Apple fixed this error shortly after its virtual assistant was first released in 2011. But a new contest shows that computers still lack the common sense required to avoid such embarrassing mix-ups. The results of the contest were presented at an academic conference in New York this week, and they provide some measure of how much work needs to be done to make computers truly intelligent. The Winograd Schema Challenge asks computers to make sense of sentences that are ambiguous but usually simple for humans to parse. Disambiguating Winograd Schema sentences requires some common-sense understanding.

In the pixelated cube world of "Minecraft," players can create almost anything their hearts desire. Now, Microsoft is using the popular world-building game to build and test artificial intelligence in the fictional environment. Microsoft has made a platform for artificial intelligence (A.I.) research using a modified version of "Minecraft" that will become available to the public following a limited release to select researchers. Project Malmo (formerly known as Project AIX) allows anyone from ambitious amateur coders to advanced computer scientists to build and test artificial intelligence in the "Minecraft" environment. "We?re trying to put out the tools that will allow people to make progress on those really, really hard research questions," Katja Hofmann, the project's lead researcher, said in a Microsoft blog post announcing the release.

A UK start-up developing artificial intelligence and machine learning for fully autonomous vehicles has received 2.7m in equity funding. The funding, led by Amadeus Capital Partners with Spring Partners and Notion Capital, will enable Bristol-based FiveAI to grow its team, step-up its development and begin simulator and road testing of its software. According to FiveAI, early approaches to autonomous vehicles have required accurate, 3D maps built using point cloud technology. In use, each vehicle then correlates against that map to work out where it is and establish a track to follow. The company is now planning a system using much stronger AI and ML to ensure that autonomous vehicles can safely and accurately navigate all environments, including complex urban ones, with simpler maps.

Does anyone have any other good sources? My main application is something similar to the example - time series financial data.

Add the Colorful Image Colorization microservice to your app today. Now, researchers and developers can train their deep learning models locally, and deploy them to Algorithmia's scalable, cloud infrastructure, where they become smart API endpoints for others developers to use. This means application developers can now obtain real-time predictions from deep learning models, and build production-ready apps using state-of-the-art machine intelligence in five-lines of code or less. Algorithms like this image colorizer join our collection of more than 2,200 algorithmic microservices.

Paul Taylor, former head of the text-to-speech group at Google and a serial entrepreneur specialising in speech, language and artificial intelligence has announced the launch of a startup which builds blockchain-based operating systems for banks and financial institutions. The startup, called ThooughtMachine led by CEO Paul Taylor, is launching its first blockchain-based operating system called Vault OS, which allows banks to run their core functions in the cloud. The core concept of Vault OS is to utilize smart contracts on a centralized and permissioned cryptographic ledger to settle all bank transactions, products, and settlements including payments, deposit accounts, savings, mortgages, loans, and credit card accounts. By relying on a scalable cloud platform, financial institutions will be able to rely on faster and more secure end to end banking systems to manage most of their operations online. Taylor believes that the Vault OS will replace outdated financial and banking systems that are still in use by the world's major banking groups.

I thought I'd write up an explanation of how Latent Semantic Indexing works since I used it in my most recent project PUBmatch.co PUBmatch.co is a tool I thought of while I was at Metis Data Science Bootcamp. You can see my slides from my presentation here. This post has a companion python notebook if you'd like to follow along here: Latent Semantic Indexing Notebook Latent Semantic Indexing appealed to me because it involves the use of Singular Value Decomposition. Singular Value Decomposition is at the heart of signal processing.

In one month from now, the second edition of the Data Science Game, an international competition of data science for students, will start (more info here). Students in last year of Masters or PhDs from all around the world will be challenged through an online competion (June 17 to July 10) and a final hackathon (september 10-11). The first 20 teams of the online phase will come to Paris to demonstrate their skills and abilities to solve a data science challenge and meet professional data scientists coming from leading companies in Data Science (Microsoft, CapGemini, Axa Data Innovation Lab, etc.). We think our participants would love to learn from your data challenge experience since you were the former top ranked kaggler. But first of all, can you quickly introduce yourself?

The recent Hadoop Summit had an amazing number of great talks, and fortunately for everyone, those are now available on YouTube! Dozens of hours of amazing content for learning every Big Data topic you can imagine from HDFS to Hive to HBase to Calcite to Spark to NiFi and beyond. The first ten videos are must watch and the rest are highly recommended. It is very hard to rate these as they are all great. Pick your topic from Machine Learning to Deep Learning to Streaming to Ingest to Security to Performance to Optimization to Programming and more.

Today Alphabet-owned Nest is launching its latest product with the debut of the previously rumored Nest Cam Outdoor, as well as a redesigned app and new features. The most notable enhancement over the original, indoor-only version of Nest Cam is necessary weatherproofing for outdoor use. With a brand new, completely weatherproof industrial design created for permanent outdoor use, Nest Cam Outdoor extends security outside the home… The weatherproof design of Nest Cam Outdoor meets the demands of a broad range of temperatures and conditions faced by outdoor cameras. There's a 1080P HD camera that gives you a 130 view and night vision via 8 built-in infrared LEDs, and a built-in speaker and microphone for talking to those outside your home. The camera has a magnetic base that Nest says is for ultimate adjustability for viewing angles, but it also means someone can technically remove the camera from the base screwed into your wall.