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Leveraging AI and Open Source

Leveraging AI and Open Source can help teams to analyze data faster, work faster, and focus on more strategic initiates. Get started today!

Published on by Pat Ramsey, Director of Technology

In the ever-evolving digital environment, businesses are constantly looking for innovative ways to enhance customer experiences. Leveraging Machine Learning (ML), Artificial Intelligence (AI), and Open Source technologies can be a powerful way to achieve this goal. ML and AI can analyze data faster and more efficiently than ever before. By leveraging AI and Open Source, businesses can create modern digital experiences that are tailored to the needs of their customers.

Artificial Intelligence vs. Machine Learning

Artificial Intelligence (AI) leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. Technically, AI describes computer programs that can make numerous complex decisions in a very short period of time. The more information the program has access to, the better it is able to make decisions, simulating how a person might learn. Artificial Intelligence is the evolution of Complex Information Processing.

Machine Learning (ML) is the process, or programming, used by AI to learn. These programs process massive amounts of existing historical data, look for patterns in the data, then use those patterns to make future predictions. With the amount of data being created and consumed each day, the availability of data has never been greater.

data statistic
How much data is created in a year?

Predictions from global data experts show that humans will produce and consume about 94 zettabytes of data by the end of 2022. 

Source: Finances Online

AI tools are used across industries such as healthcare, transportation, and finance. With these tools, businesses can make predictions related to things like customer behavior, marketing strategies, and supply chain logistics, which are incredibly useful for business operations and increased conversions. Because of this, AI can also be used to personalize customer experiences by improving support interactions and recognizing purchase patterns. With every day that goes by, you can see AI at work. Gartner estimated that by 2021, 80% of developing technologies will have AI foundations.

Open Source AI Frameworks


Amazon Sagemaker Logo

A component of Amazon's machine learning platform, Amazon SageMaker Neo, was Open Sourced as a service. Developers will be able to train machine learning models and use them anywhere in the cloud thanks to the recently published Neo-AI project. The Neo-AI project is designed with Internet of Things (IoT) sensors in mind, the type that require quick and low-latency predictions. Amazon’s AI platform keeps growing, now including support for AI-powered code generation, ML model creation, and human-like text processing.



A large number of well-known businesses, like Airbnb, eBay, DropBox, and others, employ Google's Open Source framework TensorFlow. To speed up development, TensorFlow tries to reduce and abstract away the complexity of machine learning algorithms. Developers and data scientists can easily build neural networks and other machine learning models to use data by using visual models and flowgraphs. For instance, Airbnb categorizes unit listing photographs using TensorFlow to make sure they appropriately depict a specific location.

Open AI

Open AI logo

GPT-3 is a machine learning model with a focus on language processing that was created by OpenAI. GPT-3 generates new text from an input text. The output text will conform to a task such as answering a question posed in the input, or filling in the blanks with additional information, or translating the input into another language, or summarizing the input, or inferring sentiments, or even crazier things like writing computer code from a hint provided in the input. This model can power personalized chat agents for Customer Service agents.

AI for Customer Service

Many brands are looking to AI to enhance customer service offerings. While humans are preferred when assisting clients with complex or unusual questions, AI systems can be leveraged for quick, general, frequently asked questions. This not only reduces time for the client in finding their answer, but also frees up the customer service reps to focus on more complex issues.

Brands that are adopting AI for customer service are highly focused on providing a seamless experience. In order for a chatbot or virtual agent to "speak" to consumers and provide everything from shipping information to product recommendations, AI tools can apply Natural Language Processing (NLP) and Natural Language Generation (NLG) learning to client interactions.

Chat bot service concept. Virtual assistant and CRM software automation technology. Customer using online service with chat bot to get supportics in Logistics, Distribution Center

NPL: Natural Language Processing is giving computers the ability to understand text and spoken words in much the same way human beings do. .

NLG: Natural Language Generation is the use of artificial intelligence (AI) programming to produce written or spoken narratives from a data set. This technology uses artificial intelligence, algorithms and other techniques to turn data into human language.

Service representatives will have more opportunities to employ their specific expertise and abilities to please consumers and foster brand loyalty when AI handles the routine questions.

Leveraging AI for your Brand

As companies continue to focus on improving the customer experience, leveraging AI can provide many benefits and help achieve this goal. Leveraging AI can help teams to analyze data faster, work faster, and focus on more strategic initiates. As technology improves exponentially, teams are becoming more efficient. Adapting strategies and processes to incorporate new digital technologies, including AI, Machine Learning, and Open Source is important for brands in every industry.

Futuristic Technology Retail Warehouse: Worker Doing Inventory Walks when Digitalization Process Analyzes Goods, Cardboard Boxes, Products with Delivery Infographics in Logistics, Distribution Center

AI Requires a Human Review

Before publishing AI content, it is best to review it to make sure it meets your standards. Only content that is of a high enough caliber to rank in the search engines and benefits your viewers should be published, regardless of the source for the content. You can generate a substantial amount of content by using AI, but finishing touches must be added by humans to ensure the content has the voice and direction best suited for your audience. Google has the ability to detect AI generated content, and while they may not down-rank such content, your content should still stand out and that's best done by a human. Highly competent copywriters, designers, and developers cannot entirely be replaced by AI. Used properly, AI tools can make jobs easier by handling the less exciting parts of the process. Allowing the team to focus on making your brand shine rather than on handling the more tedious tasks.

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