The goal of the article is to help you find a dataset from public data that you can use for your machine learning pipeline, whether it be for a machine learning demo, proof-of-concept, or research project. It may not always be possible to collect your own data, but by using public data, you can create machine learning pipelines that can be useful for a large number of applications. Without data you cannot be sure a machine learning model works. However, the data you need may not always be readily available. Data may not have been collected or labeled yet or may not be readily available for machine learning model development because of technological, budgetary, privacy, or security concerns. Especially in a business contexts, stakeholders want to see how a machine learning system will work before investing the time and money in collecting, labeling, and moving data into such a system. This makes finding substitute data necessary. This article wants to provide some light into how to find and use public data for various machine learning applications such as machine learning demos, proofs-of-concept, or research projects.

Ali Ghodsi loves coding and creating things that have a massive impact on the world. One famous VC made him an offer he couldn't refuse. Ali is now co-founder and CEO of Databricks which is worth almost $3 billion. In our recent interview on the DealMakers Podcast, Ali Ghodsi shared how he got started in tech, what made him leap into business, what it takes to raise half a billion dollars and become the CEO of a successful hyper-growth company. Ghodsi was born in the middle of the revolution in Iran.

The potential use of drones to cripple as much as half of Saudi national oil production this week highlights a growing threat in modern-day conflict. The attack has shown that Saudi Arabia -- the world's third largest defence spender -- is incapable of defending arguably its most protected non-military installation in Abqaiq. It is estimated to have halted around 5 per cent of international crude output, has shocked markets and spiked prices globally. Only a decade ago, such an attack by a low-cost, remote weapon systems was largely unthinkable. And players on the world stage have seized on the shift, with groups such as Islamic State and Mexican drug cartels creating their own improvised explosive vehicles from rudimentary hobby kits purchased online and in stores.

While robots have taken many of the jobs of the manually skilled, Pluribus and its future generations are coming for the jobs at the other end of the spectrum--the brilliant, the cunning, the creative. Have we reached an artificial intelligence (AI) milestone overload? Are we so jaded about momentous breakthroughs in AI capabilities that we no longer acknowledge them with the appropriate awe AI demands? One would think so after the July performance of Carnegie Mellon and Facebook's Pluribus went virtually unnoticed. You should, because this valedictorian of machine learning is a serious threat to your livelihood.

While robots have taken many of the jobs of the manually skilled, Pluribus and its future generations are coming for the jobs at the other end of the spectrum--the brilliant, the cunning, the creative. Have we reached an artificial intelligence (AI) milestone overload? Are we so jaded about momentous breakthroughs in AI capabilities that we no longer acknowledge them with the appropriate awe AI demands? One would think so after the July performance of Carnegie Mellon and Facebook's Pluribus went virtually unnoticed. You should, because this valedictorian of machine learning is a serious threat to your livelihood.

Mindar is the name of a new priest tasked with delivering sermons and overseeing religious ceremonies at a 400-year-old Buddhist temple in Kyoto, Japan. Mindar is a reported $1 million carefully crafted, female voice-praying bit of steel and silicon. "This robot will never die," said Tensho Goto, the chief steward at the temple, Vox reported. "It will just keep updating itself and evolving. With [the infusion of artificial intelligence], we hope it will grow in wisdom to help people overcome even the most difficult troubles.

The analysis in this report draws on the results of a global online survey of 289 senior IT executives working in the transportation industry. They include CIOs, CTOs, and other C‑level roles, as well as IT directors, network managers, and other direct reports into the C‑suite. The survey was conducted in August 2018 on behalf of AT&T Business by Longitude, a Financial Times company that has world-class expertise in quantitative and qualitative research. Respondents were based in 3 territories: North America (47%), EMEA (42%), and Asia Pacific (11%), and all work in large organizations that have annual revenues of USD1 billion or more. Up to now, the transportation industry has dealt pretty well with potentially disruptive technologies. For example, airlines, trucking companies, and railways have vast experience in using sensor-based tracking systems such as RFID and GPS, or automated equipment tracking, to make sure their asset utilization and operating efficiency are on-point.

Two years after Vishal Sikka stepped down as the CEO and executive vice chairman of Infosys, an Indian IT services company, he has launched a new venture in artificial intelligence. Vianai, a Palo Alto, Calif.-based startup, last week announced its arrival with $50 million in seed financing. Sikka believes AI has the potential not just to transform business but also to "amplify humanity," as he puts it. He sees AI as a force multiplier that can tackle issues ranging from climate change to self-improvement. "I would love to see tens of millions of people to be able to build intelligent systems, and billions to be able to bring basic intelligence into anything that they do," he says. Sikka, who holds a Ph.D. in AI from Stanford University, demonstrated the Vianai platform at a keynote address at the Oracle OpenWorld conference on September 17. Before his tenure at Infosys, he spent 12 years at German software company SAP, where he was last a member of its executive board. Sikka also serves on the supervisory board of the BMW Group and as an advisor at the Stanford Institute for Human-Centered Intelligence (HAI).

Schlumberger, Chevron and Microsoft have launched a cloud-based artificial intelligence platform to improve a digital services in the oil field. The companies issued a joint statement from the SIS Global Forum in Monaco announcing the launch of DELFI, a cloud-based platform loaded with software for exploration, development, production, storage tanks and pipeline projects. "Never before has our industry seen a collaboration of this kind, and of this scale," Schlumberger CEO Olivier Le Peuch said in a statement. "Working together will accelerate faster innovation with better results, marking the beginning of a new era in our industry that will enable us to elevate performance across our industry's value chain." Service Sector: Millennials now make up majority of Schlumberger's workforce Initially developed by Schlumberger for Chevron, DELFI resides entirely on Microsoft's Azure cloud computing platform.

A person receives a test for diabetes during Care Harbor LA free medical clinic in Los Angeles, California September 11, 2014. DreaMed Diabetes, the Petah Tikva-based developer of personalized diabetes management solutions, has received US Food and Drug Administration (FDA) clearance for its artificial intelligence-powered insulin recommendations technology. The company's AI-based insulin dosing decision-support software, DreaMed Advisor Pro, aims to assist people with Type 1 diabetes (T1D) using insulin-pump therapy with continuous glucose sensors or blood glucose meters.