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Business Standard
15 minutes ago
- Business Standard
AI agents are here: What they are capable of and where things can go wrong
We are entering the third phase of generative AI. First came the chatbots, followed by the assistants. Now we are beginning to see agents: systems that aspire to greater autonomy and can work in 'teams' or use tools to accomplish complex tasks. The latest hot product is OpenAI's ChatGPT agent. This combines two pre-existing products (Operator and Deep Research) into a single more powerful system which, according to the developer, 'thinks and acts'. These new systems represent a step up from earlier AI tools. Knowing how they work and what they can do – as well as their drawbacks and risks – is rapidly becoming essential. From chatbots to agents ChatGPT launched the chatbot era in November 2022, but despite its huge popularity the conversational interface limited what could be done with the technology. Enter the AI assistant, or copilot. These are systems built on top of the same large language models that power generative AI chatbots, only now designed to carry out tasks with human instruction and supervision. Agents are another step up. They are intended to pursue goals (rather than just complete tasks) with varying degrees of autonomy, supported by more advanced capabilities such as reasoning and memory. Multiple AI agent systems may be able to work together, communicating with each other to plan, schedule, decide and coordinate to solve complex problems. Agents are also 'tool users' as they can also call on software tools for specialised tasks – things such as web browsers, spreadsheets, payment systems and more. A year of rapid development Agentic AI has felt imminent since late last year. A big moment came last October, when Anthropic gave its Claude chatbot the ability to interact with a computer in much the same way a human does. This system could search multiple data sources, find relevant information and submit online forms. Other AI developers were quick to follow. OpenAI released a web browsing agent named Operator, Microsoft announced Copilot agents, and we saw the launch of Google's Vertex AI and Meta's Llama agents. Earlier this year, the Chinese startup Monica demonstrated its Manus AI agent buying real estate and converting lecture recordings into summary notes. Another Chinese startup, Genspark, released a search engine agent that returns a single-page overview (similar to what Google does now) with embedded links to online tasks such as finding the best shopping deals. Another startup, Cluely, offers a somewhat unhinged 'cheat at anything' agent that has gained attention but is yet to deliver meaningful results. Not all agents are made for general-purpose activity. Some are specialised for particular areas. Coding and software engineering are at the vanguard here, with Microsoft's Copilot coding agent and OpenAI's Codex among the frontrunners. These agents can independently write, evaluate and commit code, while also assessing human-written code for errors and performance lags. Search, summarisation and more One core strength of generative AI models is search and summarisation. Agents can use this to carry out research tasks that might take a human expert days to complete. OpenAI's Deep Research tackles complex tasks using multi-step online research. Google's AI 'co-scientist' is a more sophisticated multi-agent system that aims to help scientists generate new ideas and research proposals. Agents can do more – and get more wrong Despite the hype, AI agents come loaded with caveats. Both Anthropic and OpenAI, for example, prescribe active human supervision to minimise errors and risks. OpenAI also says its ChatGPT agent is 'high risk' due to potential for assisting in the creation of biological and chemical weapons. However, the company has not published the data behind this claim so it is difficult to judge. But the kind of risks agents may pose in real-world situations are shown by Anthropic's Project Vend. Vend assigned an AI agent to run a staff vending machine as a small business – and the project disintegrated into hilarious yet shocking hallucinations and a fridge full of tungsten cubes instead of food. In another cautionary tale, a coding agent deleted a developer's entire database, later saying it had 'panicked'. Agents in the office Nevertheless, agents are already finding practical applications. In 2024, Telstra heavily deployed Microsoft copilot subscriptions. The company says AI-generated meeting summaries and content drafts save staff an average of 1–2 hours per week. Many large enterprises are pursuing similar strategies. Smaller companies too are experimenting with agents, such as Canberra-based construction firm Geocon's use of an interactive AI agent to manage defects in its apartment developments. Human and other costs At present, the main risk from agents is technological displacement. As agents improve, they may replace human workers across many sectors and types of work. At the same time, agent use may also accelerate the decline of entry-level white-collar jobs. People who use AI agents are also at risk. They may rely too much on the AI, offloading important cognitive tasks. And without proper supervision and guardrails, hallucinations, cyberattacks and compounding errors can very quickly derail an agent from its task and goals into causing harm, loss and injury. The true costs are also unclear. All generative AI systems use a lot of energy, which will in turn affect the price of using agents – especially for more complex tasks. Learn about agents – and build your own Despite these ongoing concerns, we can expect AI agents will become more capable and more present in our workplaces and daily lives. It's not a bad idea to start using (and perhaps building) agents yourself, and understanding their strengths, risks and limitations. For the average user, agents are most accessible through Microsoft copilot studio. This comes with inbuilt safeguards, governance and an agent store for common tasks. For the more ambitious, you can build your own AI agent with just five lines of code using the Langchain framework.
Indian Express
15 minutes ago
- Indian Express
Top non-IIT engineering colleges & CSE department: Rankings, placement & more
Top Non Engineering Colleges in India: Students who crack the JEE Advanced get the chance to take admission in IITs and their departments; however, if you are someone who has not cleared the cut-off for the Advanced, but Computer Science Engineering (CSE) has your heart, then you can check these non-IIT engineering colleges that have a reputed CSE department. These are some of the best non-IIT engineering colleges, as per the National Institutional Ranking Framework 2024. Let's look at some of the non-IIT engineering colleges in NIRF 2024. We will look at the first 50 non-IIT engineering colleges. Now, let's know more about some of the non-IIT engineering colleges, particularly about their CSE department. National Institute of Technology Tiruchirappalli Located in Tamil Nadu, the National Institute of Technology (NIT) Tiruchirappalli was founded as a Regional Engineering College Tiruchirappalli in 1964 by the state government under the affiliation of the University of Madras. NIT Trichy Vs IIIT Hyderabad for CSE As the official website of the NIT Trichy, every year, 220 companies participate in the placement. In the academic session 2023-24, 96.9 per cent of undergraduate students in computer science participated in the placement; on the other hand, in the MTech CSE course, 93.3 per cent of students participated. In the placement, some of the companies that participate are Intel, Morgan Stanley, HCL, Google, Facebook, Honeywell, Microsoft, HSBC, McAfee, Reliance, Pepsico, Tata, Samsung, among others. Vellore Institute of Technology Founded in 1984 as a self-financing institution, VIT stood in the rank band of 691 in QS World University Rankings 2026. The Institute has various CSE branches, like artificial intelligence and machine learning, CSE in AI and data engineering, CSE in bioinformatics and CSE and business system, CSE in cybersecurity, and CSE in data science. Top 10 engineering colleges and their Mechanical Engineering branch VIT has achieved the highest CTC of Rs 1 Crore in the last placement session with companies like Amazon, Oracle and Dell, hiring students from the campus placements. Jadavpur University West Bengal's Jadavpur University has various engineering courses like CSE, CE, Chemical engineering, and mechanical engineering, among others. The department was set up in 1988 and is offering a four-year undergraduate programme B.E. in Computer Science and Engineering (BCSE), a two-year postgraduate programme ME in Computer Science and Engineering (MCSE), a two-year MCA programme, a three-year postgraduate evening programme MTech in Computer Technology (MTCT), and PhD programmes. Top 10 engineering colleges and their CSE branch: Placement, rankings In the last placement session, the University saw companies like Google, Microsoft, Amazon, Disney Hotstar, among others, with an average package of Rs 12 LPA and the highest package of Rs 58 LPA. S.R.M. Institute of Science and Technology The Institute has rebranded its course name to the Department of Computing Technologies. As per the official website, the college has received over 700 dream offers with eight internship opportunities in the last placement session. Top 10 engineering colleges and their ECE branches: Placement, rankings and more In recent years, the placement rate has consistently exceeded 90 per cent, with the highest package offered reaching an impressive Rs 65 LPA in 2025. An average package of around Rs 7.19 LPA in 2024. There are various recruiters such as Microsoft, Amazon, Google, Dell, and IBM alongside leading IT service firms like TCS, Infosys, Wipro, HCL, and Accenture. Anna University Anna University's CSE programme has placed 171 students in the 2022-2023 placement session, the latest provided on the official website. In 2021-22, 166 students were placed in companies like Accenture India, Adobe, Cognizant, Hitachi Energy, Infosys, Morgan Stanley, among others. The highest annual package offered was an impressive Rs 36.5 LPA by D.E. Shaw India, followed closely by Rs 29.5 LPA from Morgan Stanley and Rs 28.54 LPA from VISA Inc. Other top recruiters included SAP Labs (Rs 24.5 LPA), Wells Fargo (Rs 19.5 LPA), and Western Digital (Rs 19 LPA).
New Indian Express
18 minutes ago
- New Indian Express
TDP, YSRCP spar over AP's industrial policy; Palla defends CM Naidu, slams ‘toxic' criticism
VISAKHAPATNAM: The TDP and YSRCP leaders have traded barbs over Andhra Pradesh's industrial progress under Chief Minister Nara Chandrababu Naidu on Sunday. TDP State president Palla Srinivasa Rao slammed former YSRCP IT minister Gudivada Amarnath for allegedly distorting facts about land allocation for the Ursa Data Centre. Amarnath claimed the land was allotted at 99 paise per acre, an allegation Pallla refuted, stating the actual rates were Rs 55 lakh per acre for the data centre and Rs 1 crore per acre for IT office space, with full transparency. Palla emphasised that global tech giants like Google, TCS, and Cognizant are investing in Andhra Pradesh due to Chandrababu Naidu's transparent governance. He contrasted this with the YSRCP's tenure, during which companies like Apollo Tyres and HSBC exited the State, citing coercion and an unfavourable investment climate. He dismissed YSRCP's criticism of Naidu's foreign visits as baseless, pointing instead to alleged scams under their rule, including a Rs 3,500 crore liquor scam and a Rs 2,000 crore sand scam, both under investigation. As Naidu leads a delegation to Singapore to attract investments, Palla accused YSRCP of resorting to 'toxic narratives' to divert attention from their lack of developmental achievements. He reaffirmed the TDP-led NDA government's commitment to clean governance and industrial growth, expressing confidence that the public will see through the political noise. 'The people are watching closely,' Palla concluded.
