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Artificial Intelligence at the speed of Machine Learning

Hypergiant combines Artificial Intelligence research from the past 80 years with big data and bleeding-edge Machine Learning techniques to invent technology that redefines how humans interact with the world.

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Robots will not take over the world; humans will--using AI as a tool, like the hammer, to build a better one.
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"Artificial Intelligence gives us a chance to regain our humanity."
-John Fremont

Hyper
Giant

The difference between Artificial Intelligence and Machine Learning is that Artificial Intelligence describes any technology that simulates human behavoir. Machine Learning--one path to AI--enables technology to learn from data with the goal of making technology more intelligent and human life more enriching.

AI-Machine Learning Techniques

  • Supervised Machine Learning

    The machine has a labeled, annotated, classified, or solved data set from which it answers directly and/or deduces the most likely answer based on existing variables.

  • Unsupervised Machine Learning

    The machine has data that is not labeled, annotated, classified, or solved. It analyzes the data set to determine structure, patterns, connections, and categorizations.

  • Reinforcement Machine Learning

    The machine learns its environment, resources, objectives, and success or failure through trial and error then makes future decisions based on its findings.

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Real-World Machine Learning Applications

AI IS NO LONGER FODDER FOR SCIENCE FICTION NOVELLAS, AND THERE IS NO NEED TO FEAR IT. AI, WHEN DEVELOPED AND ADOPTED BY ETHICALLY SOUND PEOPLE, DRASTICALLY IMPROVES HUMAN LIFE.

Speech Recognition

Many consumers welcomed new family members, Alexa and Siri, into their lives.

More than making information as readily available as a wake-word, digital voice assistants make life more convenient overall through machine learning that enables intelligent, humanistic speech recognition. Sure, they can recite the height of Everest or translate your favorite french poem in their soothing, motherly voices. They can also order groceries, activate your robot vacuum, and contact help in an emergency. Companies identify trends in common requests and make enhancements based on new requests.

Image Recognition

Those of us familiar with social media sites are no strangers to the facial recognition AI behind tag suggestions and Snapchat filters.

Supervised machine learning enables AI to recognize people, places, and objects from a predefined dataset—distinguishing between their unique nuances. The AI responds by directly identifying the subject or it deduces based on the existing variables. Imagine the usefulness of image recognition in search-and-rescue missions or in sending robots to scan environments for dangerous elements.

Genomics

When scientists applied machine learning (circa 1986) to DNA sequencing, results skyrocketed from 24 nucleotides discovered manually in 1967 to 14,000,000 discovered in 1990.

In 2003, the human genome project sequenced all 3 billion base pairs of human DNA, a seemingly impossible feat. Today, scientists apply machine learning to Genomics to identify markers for disease and disability, hone potential cures, predict likelihood for disease and disability, develop precise pharmaceuticals, and help consumers manage their health pro-actively.

Oil & Gas

Despite technological progress in the extraction, production, and refinement of oil and gas, we still rely on humans to perform potentially life-threatening jobs related to this field.

Instead, imagine robots that explore these dangerous environments, determine ground depth and composition, and calculate the most effective plan. Reinforcement Machine Learning enables technology to discover the most efficient, effective path to success—as well as the most efficient, effective path to avoid failure (e.g. not getting the fuel or its destruction in trying).

Weather & Climate Control

Accurate weather prediction is an incredibly complex problem to solve, and we should all appreciate just how correct weather forecasts are much of the time.

Consider: there are myriad, distinct weather data and near limitless combinates of such. How do moon phases impact atmospheric pressure which impacts water temperature which impacts tropical tornadoes which impact winds around the world? Unsupervised Machine Learning goes a long way in organizing weather’s big data, recognizing patterns, and identifying new data to improve its ability to make more precise predictions.

Automotive

According to the national safety council, we lost 40,100 mothers, fathers, daughters, sons, brothers, sisters, family, and friends to automobile accidents, in 2017.

Nearly 5 million more were seriously injured. Costs exceeded $4.8 billion. Supervised, Unsupervised, and Reinforcement Machine Learning inform the world’s first autonomous vehicles. We already see hands-free features such as parallel parking and crash-preventing braking. While we have quite a few years to go before we completely delegate driving to AI, imagine how many lives we can hold onto.

Data is the element that informs Machine Intelligence.

Hypergiant relies on two models:

Predictive Analytics & Correlative Analytics

Predictive Analytics

Predictive Analytics

  • EXTRACTING MEANINGFUL INFORMATION FROM DATASETS TO CREATE A MODEL THAT CAN PREDICT FUTURE PROBABILITIES, I.E. NAÏVE BAYES.
Correlative Analytics

Correlative Analytics

  • EXTRACTING MEANINGFUL INFORMATION FROM DATASETS TO CREATE A MODEL THAT IDENTIFIES CORRELATIONS TO MAKE PREDICTIONS, I.E. CLUSTERING.
Machine Intelligence Techniques