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McDonald’s Embraces Artificial Intelligence for Fast Food

By now you’ve seen the big news about the world’s largest fast-food chain by revenue.

Or extreme (and inadvertent) advances in food preservation technology, such as the McDonald’s hamburger and fries on permanent display with a live feed that shows them in still near-perfect (if a little pale) condition after the last restaurant closed in Iceland about 10 years ago to the day: But one of the biggest reasons for why you should care that McDonald’s is making technology core to its business is that it is one of the loudest signals to date that AI truly is the new electricity that will power the global economy in the coming decades.

If you’re living off dividends, that income growth well exceeds inflation which means you’re able to live a better quality of life. Such increases happen because the company is becoming pretty optimistic about the future, having seen 17 consecutive quarters of global comparable sales growth.

They almost don’t know that this experience is happening for them, as we’ve got dynamic digital menu boards, and effectively as they start to place their order, the menu boards respond to that ordering process and therefore are more likely to suggest items that customer will want and less likely to show items that customers less likely to want.

McDonald’s currently has one of the slowest drive-thrus among its fast-food cohort, though car idling times throughout the quick-service restaurant industry have been climbing for years, slowing down by another 20 seconds in 2019, according to QSR Magazine.

More recently, Domino’s rolled out a computer vision technology in its Australian and New Zealand stores that uses cameras to quality check every pizza to ensure the cheesy pies have been made correctly and with the right amount of ingredients.

And, by the way, Domino’s has seen its value rise dramatically in the last five-plus years: Good Times Restaurants (GTMI) is another player in the fast-food industry that is using voice assistant tech to replace supplement its human labor force.

Valyant’s AI-based voice assistants are built using actual customer recordings in order to ensure accuracy and eliminate AI bias, according to the company, which claims, based on the Good Time pilot in Denver, that Holly has an average attempted upsell rate of 43%, which puts it in the top third of the industry.

For instance, the Algo platform helps predict customer flow to help organize food prep, while also optimizing food-delivery routes based on traffic and other factors. The company claims Algo can run 1.2 quintillion (1.2 followed by a lot of zeros) different dispatching options, even on outdated hardware.

In the last few years, we’ve witnessed the increasing automation of retail, from automated checkout systems to shoplifting prevention, so we’re finally seeing the fast-food industry make similar moves in what is probably a slightly more complex environment for machines to maneuver.

For example, McDonald’s outright says that “delivery is another area where we’ve moved rapidly to capture changing consumer habits around service and convenience.” The company expects delivery orders to drive $4 billion or roughly 4% of its global sales, which is up from $1 billion just three years ago.

Cancer researchers embrace AI to accelerate development of precision medicine

Biomedical researchers are embracing artificial intelligence to accelerate the implementation of cancer treatments that target patients’ specific genomic profiles, a type of precision medicine that in some cases is more effective than traditional chemotherapy and has fewer side effects.

The potential for this new era of cancer treatment stems from advances in genome sequencing technology that enables researchers to more efficiently discover the specific genomic mutations that drive cancer, and an explosion of research on the development of new drugs that target those mutations.

To harness this potential, researchers at The Jackson Laboratory, an independent, nonprofit biomedical research institution also known as JAX and headquartered in Bar Harbor, Maine, developed a tool to help the global medical and scientific communities stay on top of the continuously growing volume of data generated by advances in genomic research.

The tool, called the Clinical Knowledgebase, or CKB, is a searchable database where subject matter experts store, sort and interpret complex genomic data to improve patient outcomes and share information about clinical trials and treatment options.

One application of this knowledgebase allows oncologists to discover what, if any, matches exist between a patient’s known cancer-related genomic mutations and drugs that target them as they explore and weigh options for treatment, including enrollment in clinical trials for drugs in development.

The core of Microsoft’s Project Hanover is the capability to comb through the thousands of documents published each day in the biomedical literature and flag and rank all that are potentially relevant to cancer researchers, highlighting, for example, information on gene, mutation, drug and patient response.

“The curator can look at this in context and, in a couple of minutes, say, ‘This is exactly what I want,’ or ‘This is incorrect.’” To be successful, Poon and his team need to train machine learning models in such a way that they catch all the potentially relevant information – ensure there are no gaps in content – and, at the same time, weed out irrelevant information sufficiently to make the curation process more efficient.

“In this case, you have to tackle some of the hard linguistic challenges head on.” Poon and his team are taking what they call a self-supervision approach to machine learning in which the model automatically annotates training examples from unlabeled text by leveraging prior knowledge in existing databases and ontologies.

Cisco survey says IT professionals are eager to embrace artificial intelligence and machine learning

With increasingly complex applications and services, IT professionals are looking to machine learning and artificial intelligence to help align their business needs.

In a survey of over 2,000 IT leaders and network strategists, Cisco found maximizing businesses' value to be IT’s top priority, which indicates a desire to drive greater innovation and closer alignment to business strategies.

Almost 40% of the survey responses named maximizing IT’s business value as their top priority, higher than simplifying operations, optimizing employee productivity and minimizing security events.

RELATED: Cisco boosts enterprise IT with new machine learning and AI software features During Cisco Live this past summer, Cisco announced new AI and machine ML capabilities to help IT teams work at machine speed and scale their work through personalized network insights.

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