If you’ve read the very excellent Technical Revolutions and Financial Capital, you know that new technologies spawn over-investment, and that over-investment leads to a lot of losers, but it lays the groundwork for the golden age of the technology to actually arrive. There is a lull between these time periods, and that is where we are with AI at the moment.

No one technology is going to solve all of the world’s problems, and achieving the SDGs will require ambitious government policies, corporate commitments and individual actions in addition to new technologies. We will need to use every tool at our disposal, and with AI becoming more powerful every day we should encourage more innovators and entrepreneurs to focus on new ways to use this technology to address our biggest societal challenges.

According to stats, nearly 73% of the everyday trading is executed by machines. Leading financial enterprises are investing in algorithmic trading because the level and volume of trade carried out by these machines is out of human bounds to process and execute

The transportation industry has already used some AI solutions for a while but it won’t be long until the increase of AI within transportation and logistics.
As A.I. is getting more subtle with time, it is a matter of time when we will get to see the exciting future driven by AI!

The rapid evolution of data science, machine learning, and artificial intelligence are paralleled in Python’s flourishing throughout the scientific community over the past fifteen years — which seems an eternity in scientific computation. Simply put, NumPy has stood the test of time

The Mayflower Autonomous Ship will collect data on the ocean and marine life, including sampling for plastics.

Captained by a robot trained by IBM-designed artificial intelligence, using a million nautical images, it will complete six months of sea trials before its two-week Atlantic crossing.

A survey conducted across nine EU countries – Belgium, Denmark, France, Germany, Italy, Poland, Portugal, Spain, and Sweden – gauged consumers’ knowledge, concern, and trust in AI and their views on a regulatory AI framework.

The cloud database company completed its IPO Tuesday at a price of $120 per share, which was followed by a closing price of $253 yesterday, valuing it at a record $70 billion

In this presentation from Digital Velocity San Diego 2019, Sanofi and their global implementation partner, Cognizant, share how they took the ‘Crawl-Walk-Run’ methodology and applied it to the organization’s technology adoption and digital Marketing analytics strategy, resulting in operational efficiencies, global data governance, customer-centric personalisation, and better ROI on marketing investments.”

Companies starting out should work closely with business teams to identify use cases and demonstrate AI’s worth through pilots. But the true value of AI can materialise only with widescale deployment when firms can offset their upfront costs with substantial business gains.