Employees toil at lines, doing the same task, repeatedly, in order to assemble a final product. A line stoppage or bottleneck can cost a fortune. What if the manufacturer could see what was going on, in real time, and fix any issues before they become real problems? Or come up with ways to make the process run smoother and more efficiently? That's the basic idea behind Drishti Technologies, a four-year-old startup cofounded by Prasad Akella, a 57-year-old Indian entrepreneur who's best known for leading the General Motors team that developed collaborative robots in the 1990s.

The Re•Work AI in Insurance Summit in New York City was held September 5–6 and saw 60 speakers from AVIVA, Travelers, GoCompare, Prudential and other insurance-related companies cover a wide range of topics -- from detecting claims fraud to applying machine learning to underwriting and maximizing revenue. Today's specialty and commercial insurance underwriters face an overwhelming number of challenges. AXIS Capital Senior Data Scientist Min Yu believes artificial intelligence (AI) will transform the specialty and commercial insurance underwriting from a "detect and repair" mode to "predict and prevent" mode. In her talk on Machine Learning to Specialty Insurance Underwriting, Yu outlined the AI process as follows: receive a submission, retrieve data, analyze risk, automate quote and quick binding. Manual underwriting would be mainly used for review, or on complicated or emerging risks.

Data centers running artificial intelligence (AI) will be significantly more efficient than those operating with hand-edited algorithm schedules, say experts at MIT. The researchers there say they have developed an automated scheduler that speeds cluster jobs by up to 20 or 30 percent, and even faster (2x) in peak periods. The school's AI job scheduler works on a type of AI called "reinforcement learning" (RL). That's a trial-and-error-based machine-learning method that modifies scheduling decisions depending on actual workloads in a specific cluster. AI, when done right, could supersede the current state-of-the-art method, which is algorithms.

In late May, Chinese facial recognition technology developer SenseTime Group announced it had raised $620 million in a second round of funding. The raise valued the company over $4.5 billion, making it the world's most valuable AI unicorn. SenseTime reportedly became profitable last year. Meanwhile, UiPath--an enterprise robotic process automation (RPA) software company--brought in $153 million in a massive Series B round led by previous investor Accel. UiPath said the round pushed it into unicorn status and followed a record year of growth.