Use Cases of Machine Learning

Use Cases of Machine Learning

Chatbots can utilize a combination of natural language processing, pattern recognition, and deep neural networks to interpret input text and offer suitable responses.

Fremont, CA: Machine learning is a subdivision of artificial intelligence (AI) focused on building applications that are smart enough to learn from data and also improve their accuracy over time without being programmed to do so. 

In the realm of data science, an algorithm is nothing but a sequence of statistical processing steps. In machine learning, algorithms are purposed to find features and patterns in massive amounts of data to make decisions and predictions on the basis of new data. When the algorithm is better, the predictions and decisions will become more accurate as it processes more data.

Here are some of the use cases of machine learning:

• Digital assistants: Google Assistant, Apple Siri, Amazon Alexa, and other digital assistants are empowered by natural language processing (NLP), a machine learning application that allows computers to process text as well as voice data and ‘understand’ human language. Natural language processing also powers voice-driven applications like speech recognition (speech-to-text) software and GPS.

• Recommendations: Deep learning models enable ‘people also liked’ and ‘just for you’ recommendations offered by Netflix, Spotify, Amazon, and other entertainment, retail, job search, travel, and news services.

• Chatbots: Chatbots can utilize a combination of natural language processing, pattern recognition, and deep neural networks to interpret input text and offer suitable responses.

• Online Advertising: Deep learning and machine learning and models are capable of evaluating the content of a web page—the topic and nuances such as the author’s attitude or opinion—and serve up advertisements customized to the visitor’s interests.

• Detecting Fraud: Machine learning regression and classification models have overthrown rules-based fraud detection systems that have a high number of false positives when flagging stolen credit card utilization and are rarely successful at detecting criminal utilization of stolen or compromised financial data.

Published at Fri, 08 Jan 2021 03:56:03 +0000

Google AI concocts ‘breakie’ and ‘cakie’ hybrid baked goods

If, as I suspect many of you have, you have worked your way through baking every type of cookie, bread and cake under the sun over the last year, Google has a surprise for you: a pair of AI-generated hybrid treats, the “breakie” and the “cakie.”

The origin of these new items seems to have been in a demonstration of the company’s AutoML Tables tool, a codeless model generation system that’s more spreadsheet automation than what you’d really call “artificial intelligence.” But let’s not split hairs, or else we’ll never get to the recipe.

Specifically it was the work of Sara Robinson, who was playing with these tools earlier last spring, as a person interested in machine learning and baking was likely to start doing around that time as cabin fever first took hold.

What happened was she wanted to design a system that would look at a recipe and automatically tell you whether it was bread, cookie or cake, and why — for instance, a higher butter and sugar content might bias it toward cookie, while yeast was usually a dead giveaway for bread.

Image Credits: Sara Robinson

But of course, not every recipe is so straightforward, and the tool isn’t always 100% sure. Robinson began to wonder, what would a recipe look like that the system couldn’t decide on?

She fiddled around with the ingredients until she found a balance that caused the machine learning system to produce a perfect 50/50 split between cookie and cake. Naturally, she made some — behold the “cakie.”

A cakie, left, and breakies, right, with Robinson.

A cakie, left, and breakies, right, with Robinson. Image Credits: Sara Robinson / Google

“It is yummy. And it strangely tastes like what I’d imagine would happen if I told a machine to make a cake cookie hybrid,” she wrote.

The other hybrid she put together was the “breakie,” which as you surely have guessed by now is half bread, half cookie. This one ended up a little closer to “fluffy cookies, almost the consistency of a muffin.” And indeed they look like muffin tops that have lost their bottoms. But breakie sounds better than muffin tops (or “brookie,” apparently the original name).

These ingredients and ratios were probably invented or tried long ago, but it’s certainly an interesting way to arrive at a new recipe using only old ones.

The recipes below are perfectly doable, but to be transparent were not entirely generated by algorithm. It only indicates proportions of ingredients, and didn’t include any flavorings or features like vanilla or chocolate chips, both which Robinson added. The actual baking instructions had to be puzzled out as well (the AI doesn’t know what temperature is, or pans). But if you need something to try making that’s different from the usual weekend treat, you could probably do worse than one of these.

 Image Credits: Sara Robinson / Google

 Image Credits: Sara Robinson / Google

Published at Fri, 08 Jan 2021 00:11:15 +0000

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