Deep Learning and AI

How Deep Learning is Shaping Every Industry

August 16, 2022 • 8 min read


With all these new technologies and buzz words flying around, the big one a lot of people are talking about is AI and deep learning. AIs from DeepMind and Open-AI are all making headlines for their impressive abilities. DeepMind's AIs can play StarCraft 2 at a Grandmaster level, while Open-AI's Dalle-2 has shown creativity in its image-generating AI.

AI (or artificial intelligence) is a code written by developers that learn the parameters of a task through inference training. Traditional coding requires the user to define the rules for which data is inputted to output an answer. Deep learning flips the script; users can input the data and the answer and the model can define its own rules.

Deep Learning vs. Traditional Coding

For example, we can consider coding live-photo Rock Paper Scissors. With infinite variations of hand variations, skin tones, and placement within the sensor, writing code to play rock paper scissors can get extremely extensive. Training a deep learning model makes this task so much easier.

With deep learning algorithms, you can input large datasets of different variations of rocks, papers, and scissors. The model can learn from your definitions by being supplied with large amounts of data and answers.

Eventually, Deep Learning and Artificial General Intelligence (AGI) will help users write code too! This is possible to a small extent with OpenAI’s GPT-3. AI models are beginning to have more artificial neural networks and parameters than the number of neurons in the human brain.

The use cases of AI and Deep Learning are only bound by our imagination. People have developed AIs to participate in forums to fool users into thinking they were real people. Or geniuses like Demis Hassabis lead the DeepMind team to develop an AI model to predict the folding of proteins.

What AI and Deep Learning Does For You

There is no major industry that has not been affected by the wonders of AI. Modern supercomputers are no longer bound by a bare metal enclosure. Connectivity and remote access through the cloud mean feeding and training your deep learning model with more data is extremely easy.

AI has changed the way people have tackled problems like data collection, analysis, and more. The deep learning model will notice patterns that we humans might not be able to see. With this added accuracy the limits of deep learning and artificial intelligence are infinite.



Traffic lights and FasTrak can utilize NLP models to determine what vehicles that pass by. The automotive industry is in the rapid development of autonomous cars and drones, getting smarter and safer each new year.

Using cameras and radars to map out surroundings continues to pour more data into the autonomous vehicle knowledge base for more and more accurate driving. AI models can ingest hundreds of data parameters to determine the best decision when operating a vehicle. As consumer vehicle autonomy advances, the technology can be implemented in commercial vehicles.



AI-powered robots in factories already work alongside humans to operate tasks such as building, assembling, sorting, stacking, and more. You can also use robots to navigate the storage floor, delivering products to certain locations for assembly, shipment, and more.

NVIDIA developed Digital Twins to help factories model a digital mirror of their operations processes. Deep Learning models can be used to identify bottlenecks in the manufacturing process within the Digital Twin. AI can be used for predictive maintenance, supply chain management, and quality control. The usefulness of an AI analysis of the manufacturing facility can highlight areas that can be optimized.



With the many fields in healthcare AI has been a huge part of them. We’ll list a few:

  • Genome Sequencing: Deep learning can improve genome sequencing by providing an accurate and automated way to identify patterns and correlations. This can help to speed up the process of genome sequencing and make it more reliable.
  • Drug Discovery: Proteins are the building blocks of life, and only recently has Artificial Intelligence helped us predict how they fold. AlphaFold by DeepMind is enabling scientists to map out proteins making strides in drug discovery.
  • Personalized Care: With constant monitoring and comprehensive patient analysis, prescriptions can be custom to each person, and allergies can be identified. Healthcare can be personalized to avoid complications delivering efficient and effective nursing.

Smartphone Applications and E-Commerce

apps & ecommerce

AI greatly benefit platforms that utilize recommendation systems to generate traffic and engagement. Music platforms like Spotify identify genres and moods from a specific user to develop relevant and curated playlists. Shoppers on Amazon can recommend products users didn’t know they wanted.

Developing a Deep Learning Model and deploying an AI with recommendation systems can gather important demographic data. With this data, the model can determine quality recommendations encouraging users to continue to use your application! More engagement means more potential sales and user satisfaction.



Nowadays, Finance applications are taking hold as the industry standards for loan decisions and planning investment portfolios. Deep Learning models and AIs can provide an unbiased outlook on a person’s eligibility and/or recommendation for stocks, removing emotion from any decision.

Since AIs are very good at noticing patterns, Fraud Protection services can become more and more accurate. They are also able to detect suspicious situations bringing light to potentially fraudulent activities for further investigation. For example, detecting money laundering can be a huge play for AI in finance, detecting suspicious over the pricing of raw materials or detecting very odd yet consistent patterns in companies bookkeeping.

Be a Part of Today and the Future

New technology has made amazing progress and Artificial Intelligence and Deep Learning are the next technological boom and we are at the start. With amazing and mind-boggling advancements and new iterations and applications applied to Artificial Intelligence and Deep Learning Algorithms, it is an exciting time to be alive.

AI may still sound far-fetched almost like Science Fiction; a computer that learns... but we want to highlight its importance. Many companies already have so much data, that finding a way to organize and feed that data to an AI can prove powerful. Plus, it’s not extremely difficult to utilize too! With the right tools and guidance, you too can develop a compelling AI model. The ideation of creating a strong AI is as easy as a couple of generic steps:

  1. Identifying the problem that the AI algorithm will solve.
  2. Collecting data that will be used to train the algorithm.
  3. Developing a model of the problem domain.
  4. Training the AI algorithm on the collected data.
  5. Evaluating the AI algorithm on unseen data to assess its performance.
  6. Refining the AI algorithm based on the results of the evaluation.

There are plenty of resources to learn how to get started with AI and deep learning. We at SabrePC would love to be your hardware/solutions provider for a deep learning AI workstation or server. If you’re just getting started with AI deep learning we offer compelling pricing and fast turnaround time, preinstalled with the latest AI development software. All our systems are customizable to accelerate your research and workflow.


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