Natural Language Processing : What makes a computer speak and understand what we say ?

We all have come across the term “ChatGPT”,”Artificial Intelligence” and its capabilities to generate texts and solutions in different domains. But, what is the technology behind ChatGPT. In a nutshell the answer to this question is simple, which is “Natural Language Processing”. We’ll take a look at what is Natural language processing and its real life application, the challenges in Natural Languages processing in brief in this newsletter.

• Natural Language Processing (NLP): It's an AI field that enables computers to comprehend and generate text and speech akin to humans, showcased in applications like Siri, Cortana, and ChatGPT.

• NLP Technology: Combines linguistic rules, statistics, machine learning, and deep learning for machines to grasp human language, understanding intent and sentiment.

• Real-life NLP Applications: Voice-operated GPS, digital assistants, chatbots, translation software, and speech-to-text tools are daily applications of NLP.

• Enterprise Integration: NLP's role extends to business solutions, enhancing productivity, streamlining operations, and simplifying critical processes.

• NLP Challenges: Irregularities in language—homonyms, idioms, grammar exceptions—pose complexities. Teaching computers to interpret these nuances is vital.

• Key NLP Tasks:

  • Speech Recognition: Converts voice to text accurately, tackling challenges like slurring, accents, and varying intonation.

  • Part of Speech Tagging: Identifies word usage and context, labeling words based on their roles like verbs or nouns.

  • Word Sense Disambiguation: Picks the right meaning of a word with multiple senses in a given context.

  • Named Entity Recognition (NER): Identifies entities in text, such as locations, names, or organisations.

  • Co-reference Resolution: Determines when two words refer to the same entity, handling pronouns and metaphors.

  • Sentiment Analysis: Extracts emotions and attitudes expressed in text.

  • Natural Language Generation: Converts structured data into human-readable language.

NLP is vital for machines to understand language complexities, enabling various applications and driving both consumer and enterprise solutions. It tackles challenges inherent in human communication, empowering machines to process, comprehend, and generate text and speech effectively.

IIT Indore collaborates with Choithram hospital to study brain disorders

• Bacterial Infections and Brain Disorders:

  • Joint research by IIT-I and Choithram Hospital suggests a link between bacterial infections, particularly Helicobacter pylori (H pylori), and brain disorders like Alzheimer's.

• Treatment Insights:

  • Findings aim to enhance early-stage Alzheimer's treatment effectiveness by understanding the impact of H pylori on brain physiology.

• Gut-Brain Axis Disruption Study:

  • Published in Virulence, the study explores the role of H pylori in disrupting the gut-brain axis, suggesting the possibility of microbial secretions entering the brain through the gut-brain nerve connection.

• Research Leadership:

  • Led by Dr. Hem Chandra Jha from IIT-I and Dr. Ajay Kumar Jain from Choithram Hospital.

• Bi-Directional Communication:

  • Gut-Brain Axis involves bidirectional communication between the central and enteric nervous systems, connecting emotional and cognitive brain centers with intestinal functions.

• Inflammation and Transcriptional Regulation:

  • H pylori infection increases gut inflammation and alters the activity of key molecules, possibly acting as a transcriptional regulator for inflammatory and Alzheimer's disease-associated hallmarks.

Google Collaborates with Rad AI to Transform Radiology Reporting Through AI

• • Strategic Alliance with Google:

    • Rad AI, a revolutionary AI startup in radiology reporting, joins forces with Google to enhance radiologists' efficiency and elevate patient care.

  • AI-Powered Platform:

    • Rad AI Reporting, already trusted by 30% of U.S. radiology practices, significantly reduces dictated words by up to 90%, alleviating radiologists' workload.

  • Integration of Google's AI Tools:

    • Collaboration involves integrating Google's MedLM and future models into Rad AI's platform for next-gen software and reporting capabilities.

  • Multi-Pronged Approach:

    • Initiatives include automating report generation, leveraging Google Cloud's ecosystem for scaling AI models, and providing intuitive tools for seamless AI integration in radiologists' workflow.

  • Mission Acceleration:

    • Partnership aims to accelerate the mission of reducing burnout, streamlining workflow, and improving patient care in radiology reporting.

Lets Make a deal : Probability in a game of guessing

• • Monty Hall Game Introduction:

    • Originated from the TV show "Let's Make a Deal" in the United States.

    • Utilized essential mathematical concepts, especially probability.

  • History and Popularization:

    • Proposed by American biostatistician Steven Selvin.

    • Popularized by Marlyn vos Savant in 1990.

    • Considered a probability paradox and statistical illusion.

  • Game Setup:

    • Three doors labeled A, B, and C.

    • One door hides a car, and the other two have goats.

    • Only the host (Monty Hall) knows where the car is.

  • Gameplay:

    • Player selects one door.

    • Host, Monty Hall, opens another door with a goat behind it.

    • Player faces a choice: stick with the original choice or switch to the remaining unopened door.

  • Probability Insight:

    • Initially, each door has a 1/3 chance of hiding the car.

    • After player's initial choice, the probability of the car being behind the chosen door is 1/3, and the other two doors collectively have a 2/3 probability.

    • When one of the other doors is revealed to have a goat, the unchosen door's probability of having the car becomes 2/3.

  • Strategic Choice:

    • To maximize the chance of winning the car, it's statistically advantageous to switch doors.

    • Probability perspective: Switching gives a 66.67% chance of winning compared to sticking with the initial choice (33.33%).

  • Conclusion:

    • The essence lies in the strategic decision to switch doors based on probability, offering a higher likelihood of winning the car in the Monty Hall Game.