Natural Language Processing

Taking linguistics to new heights

Deciphering human intent through the medium of words

Whitepaper: Deep Fakes and How they will Change the World

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Natural language processing meets real-world client experiences

Helping clients realize the benefits of their AI applications.

Explanation of NLP

Natural Language Processing or NLP is an area of machine learning designed to understand the intended message of the human. Imagine someone says to you “that’s hot” vs “it’s hot”, as a human we know the difference between the two, but for computers, it could not comprehend the difference.  When we are saying “it is hot”, we are not only making a complaint about the weather but also the sentimentality of the statement is negative. In contrast, “that’s hot” is a very positive statement to make about something. The ability for a computer system to accurately make this distinction is the lynch pin for many advances in artificial intelligence to take hold.

Benefits of NLP

  • Applying sentiment analysis to all correspondences
  • Capability to identify problem interactions in real time
  • Can read large volumes of data and highlight what's important
  • Highly customized communications with staff or customers
  • Effective at providing highly accurate responses to queries
  • Alleviates need for management to closely watch staff
  • Protects from liability by identifying phrases violating HR policies

Challenges of NLP

  • A very small stage in a vast cosmic arena tendrils of gossa Requires time and resources to train the NLP System with data specific to the enterprise
  • Manpower able to effectively deploy NLP is very limited
  • Hardware costs to perform initial training may be cost prohibitive
  • Off the shelf pre trained NLP systems accuracy may suffer
  • Ethical considerations may apply to using machines as oversight

NLP breakthrough: LSTM

For many years recurrent neural networks were used for natural language processing with varying degrees of success. The main issue was that as sentences grew larger, the requirements to train the neural networks grew exponentially making it impractical to create truly perceptive NLP systems. In 2017 the Google Brain team developed transformers, a form of machine learning that leveraged long short-term memory (LSTM) that helped to greatly reduce the computational requirements to understand words and phrases. Although the proliferation of this technology is quite limited the systems that use it are very impressive.

$43Billion

The global NLP market was estimated at $5B in 2018 and is expected to reach $43B by 2025

2022 AI Multiple “Top 30 NLP Use Cases”

NLP and AI Services for personalized solutions and efficient user experiences.

Leverage the power of NLP and AI to transform and analyze unstructured data.

We offer advanced Natural Language Processing (NLP) and AI services that use machine learning and deep learning algorithms to deliver effective and personalized solutions. Our expertise in NLP allows us to develop powerful tools and techniques that enable us to transform and analyze unstructured data such as text, speech, and images. We can help you make sense of your data by using techniques like text mining, sentiment analysis, Named Entity Recognition (NER), text classification, topic modeling, and information retrieval. With our experience in building intelligent chatbots, voice assistants, and intelligent virtual assistants, we can help you create a more efficient and personalized user experience.

We also have extensive knowledge in speech recognition and dialogue systems, which enables us to build systems that can understand and respond to human speech in natural language. Our services in this area are designed to help you leverage the power of NLP and AI to improve your business processes and provide your customers with the best possible experience.

Deep Fakes and How they will Change the World

This whitepaper explains and showcases deepfakes, which is a new wave of visual and audio forms artificial intelligence. It highlights the impacts and challenges it poses for the next decade.

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