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India Today
3 days ago
- Business
- India Today
IIT Delhi launches six-month executive course in generative AI for professionals
To cater to the surging demand for skilled professionals in the evolving field of artificial intelligence, the Indian Institute of Technology Delhi (IIT Delhi) has rolled out the second edition of its Certificate Programme in Generative AI. Offered under its Continuing Education Programme (CEP), the six-month online course is crafted for working professionals seeking cutting-edge expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and ethical AI sector-agnostic programme is tailored for individuals across domains including software engineering, data science, machine learning, digital product management, and applied research. It also welcomes educators and tech-savvy professionals aspiring to pivot into advanced AI are trained in key AI tools such as Python, NumPy, TensorFlow, PyTorch, spaCy, and Hugging Face. The curriculum includes hands-on tutorials and industry-inspired capstone projects designed to simulate real-world AI applications across verticals like healthcare, education, finance, and autonomous systems. The comprehensive coursework covers advanced topics such as neural network development, transformer-based architectures, multilingual NLP, and parameter-efficient fine-tuning (PEFT) for low-resource settings. Participants also delve into modern model architectures like GPT, BERT, and T5, while exploring frontier techniques such as instruction tuning, retrieval-augmented generation (RAG), reinforcement learning with human feedback (RLHF), and advanced prompting strategies to boost model performance and the broader impact of the programme, Professor Tanmoy Chakraborty from the Department of Electrical Engineering at IIT Delhi shared, 'This programme is rooted in our belief that Generative AI will be at the heart of future innovation and decision-making. We're committed to nurturing professionals who can not only understand AI technologies but also lead their application across industries with accountability and depth.'As AI continues to reshape the global landscape, industry reports have underscored the critical need for AI talent. A PwC analysis projects AI to add up to USD 15.7 trillion to the global economy by 2030. However, a BCG study points out that while AI investments are rising, only 26% of organisations are successfully scaling these technologies for real value. Meanwhile, EY's The AIDEA of India report suggests that Generative AI alone could contribute USD 1.5 trillion to India's GDP by the end of the programme is delivered through a blend of live online classes and self-paced learning, offering 60 hours of instructor-led sessions, structured tutorials, and a 10-hour capstone project. Participants also have the opportunity to engage in an optional one-day campus immersion at IIT Delhi, gaining exposure to the institute's academic and research enrol, candidates must hold an undergraduate or postgraduate degree in science, technology, engineering, or mathematics. Upon successful completion, learners will receive an e-certificate from IIT Delhi a focus on practical skill-building and responsible innovation, this programme aims to shape the next generation of AI leaders equipped to drive meaningful transformation across industries.- EndsMust Watch
The Hindu
5 days ago
- Business
- The Hindu
AI in legal education: Industry experts highlight need for AI literacy in law schools
The integration of Artificial Intelligence (AI) into legal education is becoming increasingly essential as the Indian judiciary grapples with persistent case backlogs. With a government allocation of ₹7210 Crore for the e-Courts Phase III project, which includes ₹53.57 Crore specifically for AI and Blockchain technologies, the legal landscape is set to undergo significant transformation. AI technologies such as Machine Learning (ML), Natural Language Processing (NLP), and Predictive Analytics are being utilised to automate administrative tasks, enhance case tracking, and improve crime prevention efforts. This shift is not limited to the judiciary; top law firms in India are also adopting AI tools to streamline research, drafting, and due diligence processes. However, this raises critical questions about ethics, bias, and the future of legal education. To prepare students for an evolving job market where AI plays a crucial role, law schools must update their curricula to include AI literacy. Students should learn how to adapt technology while preserving core legal principles and enhancing their critical assessment skills. The Hindu hosted a webinar titled 'Gamechanger: Teaching AI to Law Students and Lawyers' on July 5 at 5:00 p.m. It featured experts like Shouvik Kumar Guha from NUJS and Sonam Chandwani from KS Legal & Associates. The discussion will focus on how law schools can implement these changes effectively. How are law firms using AI? According to Ms. Chandwani, AI is very beneficial for students aiming to join law firms, as law firms have evolved, and so have their expectations from new hires. She emphasized that legal education must become more aligned with practical industry needs. Ms. Chandwani stressed the need for AI literacy. She said that students should learn AI basics in plain terms, like how machine learning can dig through court rulings or predict outcomes, or how natural language processing speeds up reading contracts under the Indian Contract Act. She said that students don't need to be tech geniuses, as that's not their forte, but just understand how AI helps firms save time and win clients. On the uses of AI at a law firm, she said, 'We use AI when we are unable to find the relevant judgments or are unable to do research within the specified time. Ms. Chandwani said these skills make new hires valuable as firms use AI to cut costs on big cases. She added, 'AI comes in handy while conducting due diligence, preparing the checklist, or going through the contract review.' Ms. Chandwani said AI can make mistakes, like giving wrong judgments. It is very important to understand and read the subject and ensure that the outcomes are efficient. Highlighting data sensitivity, she said firms handle private clients' data, so they face hefty fines in case there is any slip-up. She added, 'Students also need to learn how to spot and fix these biases to keep firms out of trouble. End-to-end job will never be possible to be done through AI.' Exploring different teaching techniques According to Mr. Guha, the legal field is changing, and once technology gets introduced in a certain field, you cannot keep tech out of it forcibly. Pointing to the limitations in current educational structures, Guha observed, 'There are law schools with over 800, 900 students in a batch. How is a teacher supposed to give personalised feedback and prepare these students specifically? This gap is something which we can try to bridge with technology.' Also Read: AI in law: Students need to sharpen critical assessment skills to make best use of technology Mr. Guha said that AI-powered tutors by no means whatsoever are a substitute for faculty, but they can guide students with additional, specific feedback. However, he said, 'Completely unregulated and unsupervised use of AI tools, especially at a formative age for law students, has the disadvantage of robbing them of some of the critical thinking power'. Mr. Guha stressed that with the advent of AI, the traditional methodology of giving students a piece of essay to write as an assignment won't work. 'Because it's too much of a temptation to just give a prompt to ChatGPT and get a 5,000-word essay in ten seconds. One of the alternative solutions that Mr. Guha explored is that he can ask the students to submit a line-by-line critique of the assignment that the large language model has produced. Also Read: Justice Unplugged: 'Law students must stay rooted in legal knowledge, not solely rely on AI' Mr. Guha elaborated, 'Students can see whether the cases which have been used are to be used in those case scenarios, whether there is an extra case the model has missed, whether there is a jump in logic that AI has made in the way it has talked about certain provisions. Are those provisions applicable here?' He added, 'So I ask for a line-by-line critique of that. And if I intend to help the student research, help the student learn about the problem more—that can get sorted that way.' Mr. Guha also pointed to the limitations of current teaching methods, stating that one of the biggest issues that we face is the lack of innovation and imagination inside classrooms. 'If I am teaching students about a certain scenario, I can use AI to come up with multiple different case studies or multiple different possible ways in which the students can attack a problem. You know, simulation techniques. There can be hundreds of different things.' Can AI perpetuate inequalities in law education? Mr. Sharma said we need to ask who has access to these tools. He highlighted disparities among Indian law schools, stating, He added that AI risks entrenching deeper academic disparities. He said, 'People who know about AI can build their resume using it. They can write articles through AI and then get them published through sham publication formats.' Moreover, he pointed out systemic divides even within the teaching staff. 'Some of the faculties are also training in AI, especially in the premier law schools, which have access to the best AI tools—they are training their students for future employment', he said.
Yahoo
04-07-2025
- Business
- Yahoo
TutorABC Launches ChatAI 1.0 Powered by TutorABC: Redefining Speaking Practice with AI Innovation
TAIPEI, July 4, 2025 /PRNewswire/ -- TutorABC, a global leader in online English and Chinese education, announces the launch of ChatAI 1.0 Powered by TutorABC. This next-generation AI voice speaking app is designed to help learners build fluency and confidence through real-time, intelligent speaking practice — while reinforcing the central role of live, professional teaching. Built as part of TutorABC's integrated learning ecosystem, ChatAI supports students between live lessons, helping them speak more, review faster, and get more value from their time with their live teachers. Samuel Yang, Co-Chairman and CEO of TutorABC: "This is a major leap forward. With real-time, natural voice conversations and instant feedback, ChatAI 1.0 uses cutting-edge AI to give every learner a smart speaking partner in their pocket. It's fast, flexible, and incredibly effective — and when combined with live teaching, it sets a new standard for how language learning can be delivered." Start 7-day free trial to experience ChatAI: ChatAI 1.0 – What It Can Do Practice Real Conversations – Talk with natural-sounding AI and adjust voice or speed Understand with Bilingual Support – Get translations and hints when you're stuck Improve How You Speak – Get pronunciation scores and sentence suggestions instantly Learn Useful Topics – Choose from 1,000+ real-world themes like business or travel All features are designed to enhance live classes with professional teachers — helping students arrive more prepared, and leave with deeper confidence. Start 7-day free trial to experience ChatAI: AI + Human = Better Together ChatAI 1.0 complements TutorABC's live instruction — including 1-on-1, 1-on-4, and group Masterclasses. Rodney Miles, Co-Chairman of TutorABC: "AI brings consistency, speed, and data-driven feedback. Our teachers bring human connection, cultural insight, and encouragement. Together, they create a learning experience that's both powerful and personal — helping students stay motivated, build real-world skills, and enjoy faster progress." TutorABC's approach ensures AI supports what matters most: meaningful time spent with real teachers. Start 7-day free trial to experience ChatAI: Ongoing Innovation TutorABC's R&D teams are continually enhancing both ChatAI and our live teaching systems using the latest advances in: Natural Language Processing (NLP) Speech recognition and synthesis (TTS/ASR) Conversational AI, pronunciation modeling, and adaptive learning engines These upgrades are built using research and frameworks from MIT, the Stanford NLP Group, and Cambridge's ALTA Institute. By improving both AI tools and the classroom experience, we're making the entire learning journey — from self-practice to live instruction with teachers — smarter, more connected, and more effective. Start 7-day free trial to experience ChatAI: Try It Free Today ChatAI 1.0 Powered by TutorABC is fully integrated into the TutorABC App. New students can access a free trial for a limited time. It's the perfect companion to live classes — offering flexible speaking practice and better results in every session with a real teacher. Start 7-day free trial to experience ChatAI: About TutorABC TutorABC is a global leader in online education, trusted by learners for over 20 years. At the core of our platform is live human teaching — delivered through 1-on-1, 1-on-4, and group Masterclasses led by certified professionals. This foundation is supported by: Smart Tools – Flashcards, podcasts, and articles AI Support – ChatAI, podcast suggestions, and roleplays Immersive Classrooms – Interactive tools and replays Dynamic Reports – Track progress and get improvement tips We also offer study abroad consulting (with 500+ university partners in the UK, US, Canada, and Australia) and corporate training used by professionals from Apple, Microsoft, TSMC, Micron, Toyota, Yamaha, Shiseido, Citibank, PCA Life Insurance, and more. TutorABC's content partners include Oxford and Cambridge University Press, ETS, Barron's, National Geographic, and global sources like CNN, BBC, The Economist, Reuters, Forbes, NBA, and MLB. View original content to download multimedia: SOURCE TutorABC Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Time of India
02-07-2025
- Business
- Time of India
How ITC is fine-tuning its consumer research practices using AI
HighlightsArtificial Intelligence is revolutionising market research at ITC by streamlining consumer behavior analysis, strategy evaluation, and performance measurement, addressing the inefficiencies of traditional methods. ITC has developed a secure internal platform to harness AI capabilities such as Natural Language Processing and Machine Learning, enabling researchers to create impactful client-facing products while maintaining a controlled experimentation environment. Key applications of AI at ITC include in-house category exploration using public domain data, sentiment analysis of customer care data, and trend tracking through social media conversations, showcasing AI's transformative potential in enhancing decision-making processes. AI is revolutionising market research at ITC , transforming how the company explores consumer behavior, evaluates strategies and measures performance. This shift addresses long-standing challenges in market research, such as the time-consuming, labor-intensive and often repetitive nature of traditional methods. The Evolution of AI in Market Research Historically, market research at ITC involved distinct phases: Exploration : Understanding issues like sales declines or brand underperformance in specific regions, or delving into target groups (homemakers, youth, etc.) and identifying trends. Evaluation : Testing new business concepts, products, packaging and marketing mixes to gauge consumer response and optimise designs. Performance Measurement: Tracking in-market performance through brand health metrics, spend analysis and retail measurements. Each phase traditionally required defining objectives, designing research, preparing instruments, analysing data and generating reports—a process that was complex, human- and time-intensive and often tedious. AI as a Game-Changer At 'The Future is AI' webinar hosted by MRSI, Vara Prasad - vice president consumer insights and analytics, ITC, highlights how AI is streamlining these processes by: Enhancing Efficiency: AI can analyse qualitative transcripts and quantitative data simultaneously. This enables a more natural, conversational flow in data collection, making analysis significantly less laborious. Accelerating Data Processing: AI and Machine Learning (ML) can quickly process vast amounts of information, a task that was previously time-prohibitive. Understanding AI's Journey AI's evolution can be traced back to the 1950s with the Turing Test. Key milestones include: 1980s: Models harnessed large datasets to identify patterns and make predictions. 2010s: Machine learning models began to mimic human brain functions, notably with unsupervised learning. 2020s: Generative AI emerged, capable of creating original, authentic content based on historical data, training, and domain knowledge. This rapid evolution is largely driven by exponential increases in computational power, which has doubled every six months since 2010. Current and Future Capabilities of AI AI is evolving from narrow AI (like customer service bots) to general strong AI (reasoning bots that handle complex data and personalise interactions) and eventually to super-intelligent AI (driving innovation and hyper-personalisation). Within five years, ITC anticipates moving into the super-intelligence phase. AI's current capabilities, directly applicable to market research, include: Facial determination Speech and text analytics Natural Language Processing (NLP) Image and video analysis Deep learning Conversational solutions These capabilities are integrated into various toolkits, allowing researchers to analyse diverse data types and address specific business problems. ITC's Approach to AI in Market Research Recognising the potential for researchers to feel overwhelmed by the sheer number of AI tools, ITC has developed its own secure internal platform. This platform allows product developers and solution teams to create impactful client-facing products while ensuring a controlled environment for experimentation. ITC's strategy involves: Computational AI: Leveraging NLP and ML for agile and predictive solutions, especially for regularly used market research applications. Generative AI: Fine-tuning general-purpose generative AI models with specific, fresh consumer data and ITC's decades of domain expertise. This is akin to training a highly intelligent new team member with specific market research knowledge. Synthetic Data: Utilising machine learning for data fusion and augmentation, including Generative Adversarial Networks (GANs) to create synthetic datasets that closely resemble real data, enhancing insights where real data might be incomplete or sensitive. Key Use Cases at ITC ITC has successfully integrated AI into several core market research functions: In-House Category Exploration: Instead of traditional immersions, ITC now uses public domain data (Google searches, social media conversations, videos, images) to understand consumer behavior. By analyzing timing, content, and emotional nuances, they precisely identify "what," "when," "why," and "who" regarding consumption patterns. This provides a clear, precise starting point for deeper research. Customer Care Data Analysis: Previously untapped audio files from 300-500 daily customer calls are now converted into text using AI analytics engines. This allows for sentiment analysis, identifying positive and negative feedback, brand mentions, consumer pain points, and product feedback—unlocking a wealth of previously inaccessible information. Trend Tracking: ITC uses AI to pull publicly available social conversations related to specific topics within defined timeframes (e.g., protein, gut health). This enables continuous tracking of trends, classifying them as emerging, mainstream, or waning, and informing business decisions. Influencing New Product Development (NPD): AI tools help streamline the NPD process. By analysing trends and market prevalence, ITC can use AI to generate concepts and packaging designs. This helps determine whether a trend is relevant, hot, and actionable for product development, integrating AI directly into the annual and quarterly NPD charters. Sales Performance Analysis and Anomaly Detection: AI is crucial for analysing vast sales data across multiple platforms. It can detect anomalies (e.g., sales drops for a specific brand or SKU in a particular market), analyse historical data to understand root causes and predict future outcomes. This capability is transforming sales reporting from dashboarding to predictive and prescriptive insights. The Future is AI-Powered ITC's experience demonstrates that AI is not just a tool but a transformative force in market research. It dramatically alters how data is explored, how marketing problems are evaluated and how performance is measured, leading to more dynamic, efficient, and insightful decision-making.
Finextra
02-07-2025
- Business
- Finextra
LSEG unvails analytics feed to decode corporate transcripts
LSEG Data & Analytics today launched LSEG MarketPsych Transcript Analytics, a cutting-edge Data and Feeds solution designed to transform corporate transcripts into structured, actionable intelligence. 0 Eric Fischkin, Director, LSEG Data & Analytics, said: 'LSEG MarketPsych Transcript Analytics gives clients a fast, systematic way to integrate the voices of corporate leaders, institutional investors, and research analysts into their strategies. By applying the latest advances in Natural Language Processing and MarketPsych's decades of experience transforming financial text into systematic inputs, the solution empowers users across investment management, ESG analysis, and risk management to uncover hidden signals and behavioral patterns at scale.' Built for an era where investor decisions are increasingly shaped by nuanced communication, the solution scores emotions, sentiment, topic relevance across corporate earnings calls, guidance updates, and other key events. Covering over 16,000 global public companies, it offers real-time insights by identifying more than 20 entity types, including companies, currencies, and commodities. The solution maps over 1,000 business topics and 4,000 discrete events.
