Cloudflare, the prominent connectivity cloud company, recently announced that it is introducing its first version of AI agents, Cloudy, to enable customers to harness AI-powered capabilities to improve management across its suite of products.

The company mentioned that the goal of this is to automate the time-consuming task of manually reviewing and contextualising Custom Rules in Cloudflare’s Web Application Firewall (WAF) and understanding Gateway policies in Cloudflare One. 

The AI agent has been added to two Cloudflare products as a beta preview and will be expanded to other products in the near future.

Cloudflare’s WAF helps customers protect their web applications from attacks like SQL injection, cross-site scripting (XSS), and other vulnerabilities. Cloudflare One is a SASE (Secure Access Service Edge) platform that helps enterprises manage the security of their employees and tools.

When it comes to WAF Custom Rules in Cloudflare, which helps tune the web traffic to the application, Cloudy will show an AI-powered overview of all the rules. The AI agent will help identify redundant rules, optimise execution order, analyse conflicting rules, and identify disabled rules.

The company stated that this feature will help security teams spend less time auditing configurations.

For Cloudflare One, the AI agent works with Cloudflare Gateway to help manage policy configurations, which helps organisations block access to malicious sites, prevent data loss violations, control user access, and more. 

With a quick summary of policies, it is easier for customers to get a clear understanding, spot misconfiguration, and find areas for improvement, stated the company.

The core of Cloudy’s functionality is Cloudflare Workers AI, which makes use of advanced large language models (LLMs) to process vast amounts of information, including its policy and rules data.

Cloudflare aims to enhance security by reducing the risk of human error using this technology.

Cognizant has announced its plans to build a 14-acre Cognizant Immersive Learning Centre (CILC) at its Siruseri campus in Chennai. The new facility is expected to train 100,000 individuals annually in AI.

Set to be completed within three years, the learning centre will be equipped with 14,000 seats, smart classrooms, incubator hubs, design thinking centres, client experience spaces, and residential accommodations. 

It will function as the primary hub supporting other training centres being set up across Cognizant’s campuses in Hyderabad, Pune, Kochi, and Coimbatore.

Ravi Kumar S, CEO, Cognizant, said “Our new state-of-the-art centres will power new skills and our culture of continuous learning, enabling our people to drive business impact for enterprises globally.”

As the central training hub for Cognizant’s school graduate program in India, the facility will also host intensive boot camps for fresh graduates. Additionally, it will serve as a collaborative space for technology partners, academia, and clients to engage in research and learning programs.

Cognizant says that the expansion in Chennai is part of its broader infrastructure growth in India. Since 2024, the company has launched new delivery centers in Bhubaneswar and Indore, with a techfin center set to open in GIFT City, Gujarat. 

The company had plans to consolidate its Chennai operations into three of its own buildings located at Madras Export Processing Zone (MEPZ), Sholinganallur, and Siruseri, with headquarters relocating to the MEPZ campus near Tambaram by December 2024.

This comes when Cognizant sold its campus in Thoraipakkam on Chennai’s Old Mahabalipuram Road to Bagmane in a ₹612 crore deal, according to a report by The Hindustan Times.

Additionally, Cognizant has upgraded nearly one million square feet at its Hyderabad facility and modernized its Kolkata campus.

Cognizant has been ramping up its focus on AI and GenAI skills, training 277,000 employees in 2024 alone, with 168,000 completing a GenAI course. To date, over 220,000 associates have been upskilled in GenAI.

Cognizant reported full-year 2024 revenue of $19.736 billion, representing a 1.98% increase compared to the previous year. 

This growth reverses the slight downward trend in 2023, when the company reported revenue of $19.353 billion, a marginal 0.39% decline from 2022 and a 4.9% revenue growth in 2022.

Oracle on Friday introduced Oracle AI Agent Studio, a platform designed to help Oracle Fusion Cloud Applications customers and partners create, deploy, and manage AI agents and agent teams. Announced at Oracle CloudWorld in London, the new platform is available at no additional cost.

Oracle AI Agent Studio provides tools for developing AI agents tailored to business needs. These agents integrate with Oracle Fusion Applications and support third-party systems. 

Steve Miranda, executive vice president of applications at Oracle, said, “AI agents are the next phase of evolution in enterprise applications. Our AI Agent Studio builds on the 50+ AI agents we have already introduced and gives our customers and partners the flexibility to create and manage their own AI agents.”

The studio includes a range of features, including agent template libraries for creating AI agents, agent team orchestration for managing multi-agent workflows, and agent extensibility for modifying pre-packaged Oracle AI agents. It also offers a choice of large language models, integration with Oracle Fusion Applications, secure third-party system connections, and built-in validation and testing tools.

Industry leaders have expressed support for the initiative. Lan Guan, chief AI officer at Accenture, said, “Agentic architectures will enter the mainstream in 2025, with three times as many organisations planning to invest compared to 2024. Oracle’s AI Agent Studio will allow us to orchestrate more powerful agents to drive productivity and growth.”

Mauro Schiavon, global chief commercial officer at Deloitte Consulting LLP, noted the challenge organisations face in managing AI agents. “Platforms like Oracle’s new AI Agent Studio can enable customisation that addresses unique business needs,” he said. Dan Priest, US chief AI officer at PwC, added, “We’re entering a period of agentic organizations that will fundamentally change how we work across functions and industries.”

Analysts see Oracle AI Agent Studio as a key development in AI adoption. Holger Mueller, vice president at Constellation Research, stated, “The evolution of AI across the enterprise is moving at a rapid pace. By enabling agents to be created, extended, deployed, and managed across the entire enterprise, Oracle will help its customers accelerate adoption and automation.”

Oracle Fusion Applications Suite continues to integrate AI capabilities, enabling organisations to manage finance, HR, supply chain, and customer experience data on a single platform.

Toyota Motor Corp is setting up its first R&D centre in India, reinforcing its commitment to the country as a key market. The facility, located in Bengaluru, will start with a team of about 200 employees and is expected to expand to around 1,000 engineers by 2027, according to Bloomberg.

The decision follows Toyota’s move last year to designate India as a hub for its operations across the Middle East, East Asia, and Oceania. This initiative is part of the automaker’s broader strategy to enhance collaboration with Suzuki Motor Corp. and establish India as a centre for clean and green technologies.

Toyota’s new R&D facility will be its third in the Asia-Pacific region outside Japan, following similar investments in China and Thailand. While initially focused on the Indian market, the centre could evolve into a global R&D hub, mirroring Mercedes-Benz’s Bengaluru facility, which employs over 9,000 people.

The automaker is yet to introduce plug-in electric vehicles in India, relying instead on gasoline and hybrid models. Toyota has also leveraged its partnership with Suzuki Motor Corp., in which it holds a 5.4% stake, to strengthen its presence in the world’s third-largest vehicle market. 

The company is closely observing Suzuki’s R&D operations in Rohtak, which is one of India’s largest auto engineering hubs, employing approximately 3,000 engineers.

Toyota previously considered establishing an R&D centre in India in 2010 but did not proceed with the plan. Now, the company is intensifying its partnership with Suzuki to integrate R&D and product development. 

A key example of this collaboration is Toyota’s upcoming Urban Cruiser EV, a rebadged version of Suzuki’s first electric vehicle, the e-Vitara. The model, set to be manufactured at Suzuki Motor Gujarat from 2025, marks the automakers’ joint efforts to enter both Indian and global EV markets.

On Thursday, a group of researchers from ServiceNow released a new foundational model, StarVector, that helps generate Scalable Vector Graphics (SVG) from text and image inputs.

Juan A. Rodriguez, an AI researcher at ServiceNow Research, announced on X about the model release and its code.

StarVector is a multimodal large language model (MLLM) designed for Scalable Vector Graphics (SVG) generation from images or text instructions. It addresses the limitations of previous SVG generation methods that often produced artifacts and struggled with SVG primitives beyond path curves. 

I’m excited to announce that StarVector has been accepted at CVPR 2025! Over a year in the making, StarVector opens a new paradigm for Scalable Vector Graphics (SVG) generation by harnessing multimodal LLMs to generate SVG code that aesthetically mirrors input images and text.… pic.twitter.com/zTquIdq3n9

— Juan A. Rodríguez (@joanrod_ai) March 20, 2025

The research paper stated that StarVector works directly in the SVG code space, leveraging visual understanding to apply accurate SVG primitives for compact, precise outputs. 

To train StarVector, the researchers created SVG-Stack, a large-scale dataset of 2 million samples. They also introduce SVG-Bench, a benchmark across ten datasets and three tasks: Image-to-SVG, Text-to-SVG generation, and diagram generation.

StarVector’s architecture integrates an image encoder to project images into visual tokens and a transformer language model to learn the relationships between instructions, visual features, and SVG code sequences. This enables StarVector to perform image vectorisation and text-driven SVG generation, producing more compact and semantically rich SVGs.

StarVector demonstrates strong performance compared to existing models in image-to-SVG and text-to-SVG tasks. As per the benchmark results, the model outperformed models like GPT-4 Vision (2023), and Potrace.

Rodriguez mentioned that even with the advancements in the model, it hallucinates, sometimes producing inaccurate details. He added that they are actively working on improving and tackling such challenges.

The model is available on Hugging Face, and its code is open-sourced on GitHub under Apache 2.0 licence.

Cohesity, a data security platform, has announced a significant expansion of Cohesity Gaia, its enterprise knowledge discovery assistant. This development introduces what is claimed to be one of the industry’s first AI-powered search capabilities for backup data stored on-premises. 

This marks a major leap in the enterprise data management ecosystem. By leveraging NVIDIA’s accelerated computing and enterprise AI software, including NVIDIA NIM microservices and NVIDIA NeMo Retriever, Cohesity Gaia seamlessly integrates generative AI into backup and archival processes. 

This enables enterprises to enhance efficiency, innovation, and overall growth potential through deeper data insights. 

Pat Lee, vice president of strategic enterprise partnerships at NVIDIA, highlighted the benefits of this collaboration, and said, “Enterprises can now harness AI-driven insights directly within their 8 to preserve data accessibility and security while unlocking new levels of intelligence.”

This solution will be compatible with Cisco Unified Computing System (UCS), Hewlett Packard Enterprise (HPE), and Nutanix and offer various deployment options.

Moreover, customers like JSR Corporation, a Japanese research and manufacturing company, are also evaluating the benefits of this solution.

As enterprises adopt hybrid cloud strategies, many retain critical data on-premises to meet security, compliance, and performance requirements. By extending Gaia to these environments, organisations can adopt high-quality data insights while maintaining control over their infrastructure.

Sanjay Poonen, CEO and president of Cohesity, also emphasised the importance of on-premises AI solutions.

Cohesity Gaia now offers enterprises enhanced speed, accuracy, and efficiency in data search and discovery. Its multi-lingual indexing and querying capabilities allow global organisations to analyse data in multiple languages.

The infrastructure is scalable and customisable to meet business requirements, with a reference architecture designed for seamless deployment across hardware platforms. 

Pre-packaged large language models (LLMs) on-premises ensure that backup data remains secure without cloud access. Its optimised architecture allows efficient searches across petabyte-scale datasets, making retrieval fast and reliable.

Anthropic, the AI startup behind the Claude family of models, has added web search to its AI chatbot Claude, a long-missing feature now available in preview for paid users in the US. According to their blog, free users and more regions will gain access soon. 

Users can enable web search in the Claude web app’s settings, allowing the chatbot to pull information from the internet when needed. Currently, the feature works only with Anthropic’s latest model, Claude 3.7 Sonnet.

This update puts Claude on par with competitors like OpenAI’s ChatGPT, Google’s Gemini, Mistral’s Le Chat, and xAI’s Grok. 

In a story by Verge, the challenges of AI search include combining probabilistic language models and web search, making accuracy unpredictable. Unlike deterministic systems, language models can vary in their responses, sometimes leading to serious errors.

Anthropic has also listed down use cases.

Claude’s web search helps sales teams follow industry trends, analysts find market data, researchers access sources and spot gaps, and shoppers compare products and prices.

The company also plans to release voice-based conversational features soon, the Financial Times reported. 

Mike Krieger, Anthropic’s CPO, said the company already has prototypes for the same and added that if Claude is autonomously operating a computer, the natural user interface is to speak to it. 

A few weeks ago, Anthropic announced a $3.5 billion Series E funding round, bringing its post-money valuation to $61.5 billion. The company also announced its newest Claude 3.7 Sonnet model, which earned widespread praise for its capabilities in tasks involving generating code.

OpenAI has launched new speech-to-text and text-to-speech models in its API, providing developers with tools to build advanced voice agents. These models improve transcription accuracy and introduce customisation options for generated speech.

The new speech-to-text models, gpt-4o-transcribe and gpt-4o-mini-transcribe, improve word error rate and language recognition compared to Whisper models. 

In its blog post, OpenAI said these advancements stem from reinforcement learning techniques and extensive training with diverse audio datasets. The models aim to improve transcription reliability in noisy environments, varying speech speeds, and different accents.

“Our latest speech-to-text models achieve lower word error rates across established benchmarks, reflecting improvements in transcription accuracy and language coverage,” OpenAI said.

Developers can now also control how the text-to-speech model speaks. The gpt-4o-mini-tts model allows developers to instruct the model to adopt different speaking styles, such as mimicking a customer service agent. This feature expands use cases in customer interactions and creative storytelling. However, OpenAI clarified that these models are limited to synthetic preset voices.

The company credits improvements in its audio models to pretraining with authentic datasets, advanced distillation methodologies, and reinforcement learning. Distillation techniques have enabled smaller models to retain conversational quality while reducing computational costs.

The new models are available to all developers through OpenAI’s API. OpenAI has also integrated these models with its Agents SDK to simplify development. For real-time, low-latency speech-to-speech applications, OpenAI recommends using its Realtime API.

Looking ahead, OpenAI plans to enhance the intelligence and accuracy of its audio models and explore custom voice options. The company is also engaging with policymakers, researchers, and developers on the implications of synthetic voices. Moreover, OpenAI intends to expand into video, enabling multimodal agentic experiences.

Perplexity AI, the AI-enabled search engine, is in talks to raise funds between $500 million and $1 billion, valuing the company at $18 billion, Reuters reported on Friday. This doubles Perplexity’s valuation, which stood at $9 billion in the previous funding round last December, after raising $500 million. Perplexity has been backed by NVIDIA, SoftBank Group, and Amazon founder Jeff Bezos. 

This development signals a growing demand for AI-powered search engine tools and applications. While Perplexity faces competition from Google’s Gemini and OpenAI’s ChatGPT Search, even Anthropic has entered the game, announcing a web search feature in its Claude chatbot. 

Besides primarily functioning as an AI-powered search tool, Perplexity also provides reasoning and deep research capabilities, among numerous other features. 

The company also recently announced that it is developing an agentic web browser called Comet. 

Last month, Perplexity also announced Sonar, its in-house AI model, which is now available to all Pro users. Subscribers can set it as their default model in settings, and it is said to perform on par with OpenAI’s GPT-4o. 

Furthermore, Deutsche Telekom, the parent company of T-Mobile, has partnered with Perplexity AI to create a next-generation AI phone. Running on a custom Magenta AI operating system, it will feature Perplexity Assistant.

CEO Aravind Srinivas, in a recent podcast, said that as a company grows bigger, maintaining the same speed and agility becomes challenging. “It’s beginning to happen already a little bit. We’re not as fast as we used to be.”

“We do have staging, deployment testing, A/B testing—all that stuff’s happening, and that’s naturally slowing us down in getting things out to production widely,” he added. Perplexity AI reportedly boasts 15 million active users on its website and the app. 

However, a recent research study highlighted the inaccuracies in AI search engines. The Tow Center for Digital Journalism – Columbia University, performed an evaluation of search tools from ChatGPT, Perplexity, Grok, DeepSeek Search, and Google’s Gemini. Ten articles from each of the 20 publishers were selected randomly, and direct excerpts were picked from those articles as input for the AI tool. 

These tools were then asked to identify the article’s headline, original publisher, publication date, and URL. The study found that collectively, these search engines provided incorrect answers to more than 60% of queries. Notably, Perplexity answered 37% of queries incorrectly, while Grok 3 answered 94% of queries incorrectly.

Accenture’s Generative AI bookings totalled $1.4 billion in Q2 FY25, up from $1.2 billion in the last quarter, signalling a sustained momentum in the AI space. 

The company announced its financial results for the second quarter of fiscal 2025, ending February 28, 2025, on Thursday, and highlighted its broad-based revenue growth across markets, industries, and service lines.

In Q2 FY25, the consulting giant reported $16.7 billion in revenue. 

Julie Sweet, chair and CEO of Accenture, credited the company’s strategic focus on reinvention for its performance. “Our second quarter results demonstrate that we continue to deliver on our strategy to lead reinvention for our clients and return to strong growth in FY25, with broad-based growth across markets, industries, and the types of work our clients seek from us,” Sweet said.

She acknowledged that trust and confidence in their unique strengths and capabilities are reflected in 32 clients with quarterly bookings over $100 million. 

The company posted strong growth in cloud, security, and creative business divisions. 

In June 2023, the company reported $100 million in pure-play generative AI projects, and the sales have nearly doubled every quarter since. In fiscal 2024, the company invested about $6.6 billion in acquisitions to strengthen its position in the IT industry and bolster its AI mission. 

Accenture expects the annual revenue to grow between 5% and 7%, compared with its prior forecast of 4% to 7%, Reuters reported. In comparison, analysts had expected revenue growth of 5.7%

Cadence Design Systems, a leading computational software company, has announced that it is expanding its multi-year collaboration with NVIDIA, focusing on accelerated computing and agentic AI. 

This partnership addresses global technology challenges by driving innovation across various industries and involves Cadence leveraging NVIDIA’s latest Blackwell architecture to accelerate its engineering and scientific solutions. 

This includes reducing computational fluid dynamics simulation times by up to 80 times, from days to minutes, and accelerating the Cadence Spectre X Simulator by up to 10 times.

Jensen Huang, NVIDIA CEO, noted, “Accelerated computing and agentic AI are setting new standards for innovation across industries.” 

Using its Fidelity CFD Platform, Cadence also successfully ran multi-billion cell simulations on NVIDIA GB200 GPUs in under 24 hours. It would have previously required a top 500 CPU cluster with 100,000 cores and several days to complete. 

The company expressed that it will continue to leverage Blackwell for simulation and help the aerospace industry reduce the amount of wind tunnel tests by reducing cost and expediting time to market.

New Era for Accelerated Computing

Additionally, the partnership involves the companies working together on a full-stack agentic AI solution for electronic and system design, as well as science applications. This will integrate Cadence’s JedAI Platform with NVIDIA’s NeMo generative AI framework and the Llama Nemotron Reasoning Model. 

Anirudh Devgan, president and CEO at Cadence, says, “We’re enabling the delivery of today’s infrastructure AI and agentic AI and transforming the principled simulations that underpin physical AI and sciences AI.”

The collaboration is expected to transform industries by enabling complex simulations that were previously impossible, driving efficiency, and fueling scientific discovery. It will also deliver breakthroughs in simulation, optimisation, and design. 

In his keynote address at the NVIDIA 2025 GTC summit, he mentioned that until now, the giant had been using general-purpose computers running software super slowly to design accelerated computers for everybody else. 

But with the entry of optimised CUDA software, “now our entire industry is going to get supercharged as we move to accelerated computing.”

Cadence Molecular Sciences (OpenEye) is also integrating NVIDIA BioNeMo NIM microservices with its cloud-native molecular design platform, Orion. Cadence has also been one of the first adopters of NVIDIA Omniverse Blueprint for AI factory digital twins. 

Cadence and NVIDIA are leading the way in creating an ecosystem of high-quality models, allowing equipment manufacturers and data centre companies to quickly create digital twins.

Bengaluru-based space tech company SkyServe announced that it is working with scientists at NASA’s Jet Propulsion Laboratory (JPL) and D-Orbit, a space logistics company, to advance Earth observation systems. 

The collaboration involves optimising and deploying AI models developed under NASA’s New Observations Strategies (NOS) initiative on D-Orbit’s ION Satellite Carrier. 

This initiative aims to create a unified network of space-borne, terrestrial, and airborne sensors for near-real-time monitoring phenomena like wildfires, floods, and urban heat islands. The company ultimately aims to support both scientific research and disaster response efforts.

The collaboration also involves harnessing edge computing to integrate and optimise AI models across diverse sensor configurations. 

SkyServe’s STORM, an edge-computing platform for satellites, enables the deploying of advanced AI applications in orbit. Complementing STORM, the SURGE software suite provides an on-ground environment to test, develop, and deploy AI models. 

Vishesh Vatsal, CTO at SkyServe, noted, “SkyServe’s technology plays a pivotal role in streamlining AI model deployment across diverse satellite platforms, ensuring consistency and efficiency.” 

D-Orbit’s ION satellite platform supports these efforts with a robust infrastructure. This collaboration also highlights the integration of Edge AI solutions with satellite platforms to address Earth observation challenges. 

The collaboration aims to enhance emergency response times and accelerate decision-making by enabling a wide range of use cases, such as detecting wildfires and tracking unregistered ships. 

By simulating space-embedded environments, SURGE ensures AI models maintain operational consistency across varied satellite platforms and computing environments. 

This collaboration is part of broader efforts to redefine the possibilities of space innovation and drive advancements in global monitoring.

In May last year, SkyServe also announced that it had successfully achieved Smart Earth Imaging in orbit, marking an important step forward in Earth observation. It demonstrated the ability to generate actionable insights from space in a fraction of the time.

A month before, it had also collaborated with D-Orbit to deploy STORM on a SpaceX-launched satellite. Within seconds of capturing imagery over the Egypt-Sinai Peninsula, STORM performed intelligent tasks onboard. 

These included error correction, cloud/water removal, and vegetation identification. The optimised data was then transmitted back to Earth compressed by 5X.

Michael Seibel steps down from the San Francisco-based Y Combinator (YC) as a group partner. After spending a decade at the accelerator, Seibel said he would move into a partner emeritus role. “The next adventure I’m excited to pursue is how I can help the government better serve its citizens,” he posted on X. 

Before joining YC, Seibel co-founded Justin.tv, which evolved into Twitch and was acquired by Amazon in 2014 for $970 million, and Socialcam, sold to Autodesk in 2012 for $60 million. 

During his time at YC, he served in various capacities, including as founder, group partner, managing director, and CEO of the accelerator. 

President and CEO Garry Tan shared a blog highlighting Seibel’s lasting impact on YC’s values, programs, and founder support.

Also, YC recently celebrated its 20th anniversary. Founded on March 11, 2005, by Paul Graham, Jessica Livingston, Trevor Blackwell, and Robert Tappan Morris, YC has played a pivotal role in nurturing early-stage startups, leading to the creation of over $800 billion in market value. Past YC alumni include Stripe, Airbnb, and Reddit.

YC held its Winter 2025 Demo Day on Wednesday, showcasing 160 new startups.

YC has shifted its focus from funding early-stage internet startups to AI startups. Group partner Jared Friedman spoke about the influence of AI within the startups as well. He said that one-quarter of the YC founders admitted that over 95% of their codebase was AI-generated. He pointed out that these were highly skilled founders who, just a year ago, would have built their products entirely on their own—but now, AI does the heavy lifting.

LinkedIn, the world’s largest professional networking platform, has unveiled its ‘Skills on the Rise’ ranking, identifying the top 15 skills professionals need to stay competitive in the evolving job market in 2025. In India, the fastest-growing skills include creativity and innovation, code review, problem-solving, pre-screening, and strategic thinking. 

With 64% of job-related skills expected to change by 2030, LinkedIn research highlights that 25% of professionals are concerned about their future skills, 60% are open to shifting industries, and 39% plan to acquire new skills. Moreover, 69% of recruiters report a gap between candidate skills and business requirements.

AI literacy is emerging as an essential competency across industries. Malai Lakshmanan, head of India engineering at LinkedIn, emphasised, “AI literacy is becoming essential, with our latest data showing a growing demand for skills like large language models (LLMs) and prompt engineering for tech roles in India. At the same time, foundational engineering strengths, such as software design and code review, remain critical for building high-quality, scalable solutions.” 

He mentioned that we are at a pivotal moment where mastery of core technology skills like design and coding is just as important as new-age AI capabilities for engineers. Professionals who combine these strengths will be best prepared to thrive in the agentic AI future that lies ahead.

As AI automates routine tasks, human-centric skills like creativity, innovation, problem-solving, and strategic thinking are becoming increasingly valuable, not just in marketing and design but also in business development and education. Communication, once primarily linked to sales and HR, is now considered critical in IT, consulting, and finance. 

AI skills are transitioning from an advantage to a baseline expectation, with 95% of Indian C-suite leaders prioritising AI proficiency over traditional experience. Skills like LLMs, AI literacy, and prompt engineering are now in high demand across industries beyond tech, including education and marketing.

Meanwhile, businesses are placing a stronger focus on customer engagement, a skill that has gained importance in sales, business development, and marketing, as companies seek to strengthen brand loyalty and foster lasting customer relationships.

Nirajita Banerjee, LinkedIn’s senior managing editor for India, advises professionals to assess their existing skillsets, highlight soft skills prominently on their LinkedIn profiles, and actively pursue learning opportunities through online courses, stretch assignments, or volunteer work. Data suggests that members who list five or more skills on their profiles receive significantly higher profile views and recruiter engagement.

LinkedIn’s List of Emerging Jobs for 2025

LinkedIn recently released a list of jobs that have gained prominence due to AI redefining hiring practices in 2025. This highlights the need for individuals to upskill and embrace new opportunities to remain competitive in the job market. 

Among the most sought-after roles is the AI engineer, who is responsible for designing and training AI models and algorithms to address complex problems and enhance system performance.

Researchers from the Hong Kong University of Science and Technology and Moonshot AI have teased a new AI model called AudioX, that generates audio and music using multimodal inputs.

AudioX is described as a unified model offering flexible natural language control and seamless processing of inputs that include text, video, image, music, and audio. This differs from the standard domain-specific models that typically focus on a single modality or a limited set of input conditions.

The research paper mentioned use cases like text-to-audio, text-and-video-to-audio, and video-to-audio with AudioX. Notably, the AI model also lets one refine existing audio through a text prompt, improve unprocessed music, and generate music from scratch.

Netizens seem excited about the demo of the model shared on the model’s GitHub repo, highlighting interesting use cases like generating audio for a tennis video:

AudioX : Anything-to-Audio Generation

Mindblowing, I could not believe that tennis example it was just too good. pic.twitter.com/EA8clWlqmF

— AshutoshShrivastava (@ai_for_success) March 19, 2025

The researchers mentioned that they aim to address the scarcity of high-quality multi-modal data, which has been a major bottleneck in the development of versatile audio generation systems. To tackle this, they curated two comprehensive datasets: vggsound-caps, with 190K audio captions based on the VGGSound dataset, and V2M-caps, with 6 million music captions derived from the V2M dataset.

“Extensive experimental results show that AudioX not only excels in intra-modal tasks but also significantly improves inter-modal performance, highlighting its potential to advance the field of multi-modal audio generation,” the research paper stated.

Currently, the code for the model is not available. The researchers mentioned it would be available on the GitHub page without specifying a timeframe or licence details.

There are various text-to-music models and some text-to-speech models available, which have seen creative use cases in the AI space. It remains to be seen how AudioX opens up more possibilities.

Fractal, a global provider of enterprise AI solutions, has announced a $20 million strategic investment in Asper.AI, one of its product companies focused on AI-driven growth solutions for consumer goods and manufacturing. The company said the investment will support Asper’s expansion, enhance product development, and scale its enterprise customer base globally.

Founded with the goal of transforming decision-making in enterprise growth, Asper.AI leverages AI across four key areas, including demand forecasting and planning, revenue growth management, inventory planning, and sales execution. 

The company operates across Bengaluru, New York, London, and San Francisco, focusing on delivering interconnected, AI-powered decisions that enhance business performance.

Pranay Agrawal, co-founder and CEO of Fractal, emphasised Asper’s rapid progress and said, “Asper has demonstrated exceptional growth and innovation in just three years. We are thrilled to continue our partnership with Asper’s team to drive the next phase of growth. The phased investment will fuel Asper’s vision, unlocking new opportunities for enterprise customers.”

Meanwhile, Asper.AI’s co-founder and CEO, Mohit Agarwal, highlighted that more than AI, consumer goods need an ally that scales with their operations, speaks their language, and turns data into actionable decisions. 

“This investment from Fractal enables us to enhance our autonomous growth AI platform, attract top talent, and expand our product offerings to meet the increasing demand for cutting-edge AI solutions,” he added. 

The company expects that developing such expertise internally demands substantial investment in AI talent, infrastructure, ongoing model training, and deep domain knowledge. 

Fractal, founded in 2022, is known for driving AI adoption among Fortune 500 companies. It has built a portfolio of AI-driven businesses, including Asper.AI, Flyfish (a GenAI platform for search and product discovery), and Analytics Vidhya (a leading data science community). It also incubated Qure.ai, a healthcare AI player focused on tuberculosis, lung cancer, and stroke detection. 

Delhi-based Rocket Learning launched ‘Appu,’ an AI-powered tutor designed to provide personalised and conversational learning experiences for children aged 3 to 6 on Wednesday. 

Developed with support from Google.org, the philanthropic arm of the tech giant, the startup aims to reach 50 million families by 2030, beginning with Hindi and expanding to 20 other languages, including Marathi and Punjabi. While Appu is already being piloted, Rocket Learning plans for wider adoption in Anganwadi centers and government-run preschools.

The company, founded in 2020, is led by Azeez Gupta, Vishal Sunil, Namya Mahajan, Siddhant Sachdeva, and Utsav Kheria. The organisation uses technology to bridge learning gaps in early childhood education. Gupta, a Harvard Business School graduate, co-founded the startup with the mission of democratising learning. Sunil, the company’s CTO, has been recognised in Forbes 30 Under 30 for his contributions to education technology.

AI for Education

“Appu is the future of learning—AI-driven, intuitive, and designed to evolve,” said Sunil. “We see adaptability as our greatest strength and personalization as the catalyst for unlocking every child’s potential. With 85% of brain development happening by age six, early childhood education is the next frontier in human capital.”

The AI tutor was built in six months with technical assistance from Google.org Fellows and a $1.5 million grant awarded in 2023 under the AI for Global Goals Impact Challenge. Appu leverages LLMs to deliver real-time, engaging lessons focused on pre-literacy, numeracy, and social-emotional skills. 

According to the National Sample Survey 75th Round report (2022), more than 40 million children in India lack access to quality preschool education, with many struggling with basic literacy and numeracy by the second grade. Rocket Learning is looking to bridge this gap through AI-based training, among other initiatives. 

Annie Lewin, Senior Director at Google.org, emphasised the significance of the project and said, “We look forward to seeing how this innovation helps shape the future of learning, as they scale their work to 20 additional languages.”

Beyond its immediate impact on education, Rocket Learning’s initiatives, including Appu, are projected to contribute $4 billion in lifetime value to India’s economy. 

Earlier this year, Google.org launched its Generative AI Accelerator program with a $30 million budget. The initiative aims to support nonprofit organisations leveraging generative AI to create widespread impact. The six-month program offered technical training, Google Cloud credits, and pro-bono assistance from Google employees, along with a share of the $30 million funding.

Tech Mahindra and NVIDIA have announced a collaboration to develop an autonomous pharmacovigilance solution for improving drug safety management. According to the company blog, the solution uses Tech Mahindra’s TENO framework alongside NVIDIA AI Enterprise software, including NeMo, NIM microservices, and AI Blueprints.

The solution is being showcased at NVIDIA’s GTC 2025.

“AI is ideal for monitoring medicines throughout their lifecycle to support safety. Integrating AI into the Tech Mahindra TENO framework with NVIDIA AI Enterprise software enhances pharmacovigilance by augmenting human capabilities to help identify potential safety issues more effectively,” said John Fanelli, vice president of enterprise software at NVIDIA.

The goal is to reduce the risk of human error. The AI system automates pharmacovigilance workflows, handling case intake, data transformation, quality control, and compliance management. In this system, AI agents classify, prioritise, and verify pharmacovigilance emails. 

According to the companies, the solution can reduce turnaround times by up to 40%, increase data accuracy by 30%, and lower operational costs by 25%. The system processes adverse drug reaction (ADR) cases and supports regulatory compliance through autonomous decision-making.

Nikhil Malhotra, chief innovation officer at Tech Mahindra, said the collaboration with NVIDIA will help the pharmaceutical industry manage large volumes of data more efficiently. By applying generative AI and multi-agent systems, they will improve drug safety.

“Together, we are revolutionising drug safety management and using the innovative AI-driven framework to develop multiple use cases for our global customers,” Malhotra said 

Alongside Tech Mahindra, Wipro has also launched sovereign AI services with NVIDIA to help governments and businesses develop country-specific AI solutions. The services use Wipro’s WeGA Studio and NVIDIA AI software to support local language models, data privacy, and AI governance. The applications include healthcare, banking, education, and emergency services, focusing on data security and sovereignty.

Tech giant Google rolled out NotebookLM’s new mind map feature on Wednesday, allowing users to see a visual summary from any source document. The topics and their related ideas are represented as a branching diagram.

Simon Tokumine, director of product management at Google Labs, took to X to make this announcement. 

Rolling out interactive Mindmaps in NotebookLM!

I'm so inspired by the Exploratorium here in SF – What if every notebook generated your own personal set of interactive understanding toys that help you learn through play? What if instead of text or images, Notebook could even… pic.twitter.com/fFJCGrv0kc

— Simon (@tokumin) March 19, 2025

As per the official documentation, one can use the mind maps feature when trying to understand the big picture of the source material, explore unfamiliar information, connect the dots, and get a structure of the information.

To generate a mind map, one needs to open an existing notebook (or create a new one). Once the source is analysed, a “Mind Map” button will appear, generating a mind map note to see the visual summary. Furthermore, one can interact with the Mind Map by zooming in/out, scrolling, expanding/collapsing branches, and clicking on the nodes to ask questions in NotebookLM chat.

The Mind Map can also be downloaded and shared as an image file. The feature will be available globally in the next seven days and should be available in some countries presently. AIM was able to access the feature, and it worked as expected.

Besides this, the company also added a new feature to Gemini, Canvas, that provides an interactive space for refining documents and code. It also enabled support for Audio Overview in Gemini. 

A user needs to select ‘Canvas’ in the prompt bar and start writing/editing documents, or code, with changes appearing in real-time. The feature also supports previews for HTML/React code.

To collaborate, one can export the output to Google Docs and share it with others.

Google has been announcing major updates across all its AI products, like Gemma 3, and new models tuned for robotics, and it appears to be getting more serious with AI updates.

California-based physical AI and robotics company Dexterity AI has launched Mech, which it claims is the first industrial superhumanoid robot designed to transform enterprise operations. 

The robot, equipped with two arms mounted on a rover, can autonomously navigate industrial sites and perform repetitive, physically demanding tasks. Mech aims to address the challenges of efficiency and workplace safety faced by enterprises globally.

Mech combines human-like dexterity with superhuman strength, capable of lifting up to 130 lbs (~58 kg) and stacking boxes as high as eight feet. It integrates seamlessly with existing industrial infrastructure and automation systems. 

Samir Menon, CEO of Dexterity, stated, “Mech represents a major leap forward in our mission to empower people with intelligent, flexible robots that safely and efficiently solve complex, labour-intensive industrial challenges.”

The robot operates autonomously using four steerable wheels and Dexterity’s onboard physical AI supercomputer, as the company mentioned on its official blog. 

It utilises AI models to tackle tasks such as palletising boxes and handling fragile packages with precision. Enhanced by 16 onboard cameras, Mech can optimise packing strategies even in extreme temperatures ranging from 32°F to 122°F.

One operator can manage up to 10 Mechs simultaneously, reducing injuries caused by repetitive stress and heavy lifting.

Its capabilities can be expanded through software updates, with the initial application focusing on truck loading. Additional apps are planned for release later in 2025.

Dexterity’s innovation marks a significant step in robotics for logistics operations worldwide. The company aims to expand Mech’s functionality to further revolutionise industrial workflows.

The company relies on the approach of physical AI infusing human-like dexterous skills, creating “any robot for any application”.

For industrial robots, Shenzhen-based UBTECH Robotics recently completed what is claimed to be the world’s first multi-humanoid robot collaborative training program at Zeekr’s 5G Intelligent Factory. Using the company’s Walker S1 humanoid robots, it portrayed collaboration across various production zones.

Moreover, in a recent interview with AIM, Satish Shukla, co-founder of industrial automation company Addverb, discussed the company’s plans to launch its humanoid this year.

He believes it will take another three to four years for humanoids to become as prevalent as humans. “For every human, we probably might have one humanoid,” he added.

Tribeca Developers, the real estate partner of the Trump Organisation in India, has launched the country’s first Trump-branded commercial project, ‘Trump World Centre,’ in Pune, as reported by Reuters.

The developers aim to generate over $289 million, or ₹1,700 crore, in sales from the project, which is being developed in collaboration with Kundan Spaces.

India has become the largest market for Trump-branded real estate outside the US over the past decade, with Tribeca leading the development of luxury residential projects in four cities through licensing agreements.

With 27 floors of office space spanning 1.6 million sq. ft, the development is expected to be completed by 2029, according to LinkedIn News.

India has emerged as the Trump Organisation’s largest real estate market outside the United States, with four luxury residential projects currently underway in Gurugram, Mumbai, Kolkata, and Pune.

The Pune office project is expected to cater to the city’s growing demand for premium office spaces, particularly from global and local IT firms. It is slated for completion in about four years, according to Kalpesh Mehta, founder of Tribeca Developers.

Mehta also revealed plans to launch three to four more Trump-branded luxury residential projects across northern and southern India in the next four to six weeks. The combined sales potential from these developments, including the newly launched office project, is projected to reach $1.15 billion.

American chip maker AMD announced a new processor on Tuesday for consumer laptops to run LLMs efficiently.

AMD Ryzen AI Max+ 395 is the most powerful x86 APU currently on the market and delivers a significant performance boost over the competition, the company claimed.

The processor is powered by 16 “Zen 5” CPU cores, 50 peak AI TOPS XDNA 2 NPU and an integrated GPU powered by 40 AMD RDNA 3.5 CUs. It has system memory options ranging from 32 GB to 128 GB of unified memory. 96 GB of it can be converted to VRAM through AMD Variable Graphics Memory.

AMD stated that the processor excels in consumer AI workloads like the llama.cpp-powered application: LM Studio, and is a significant upgrade for thin and light devices.

To demonstrate the performance capabilities, AMD used the ASUS ROG Flow Z13 laptop with 64 GB of unified memory. 

AMD claims the processor is up to 4x faster than the competition in time-to-first token benchmarks when using smaller models like Llama 3.2 3b Instruct. When considering 7/8 billion parameter models like DeepSeek R1 Distill Qwen 7b and 14 billion models, the ASUS laptop is up to 9.1x and 12.2x faster, respectively.

The company shared benchmarks with vision models and claimed that the Ryzen AI Max+ 395 processor is up to 7x faster in IBM Granite Vision 3.2 3b, up to 4.6x faster in Google Gemma 3 4b, and up to 6x faster in Google Gemma 3 12b. One can see the processor running the Google Gemma 3 27B Vision model in the official demo:

In addition to the new processor, AMD highlighted EPYC CPUs benchmarks that outperformed Nvidia’s Grace Superchip for enterprise AI use cases. The company also announced on Monday that AMD Versal AI Edge XQRVE2302 SoC is their second flight-qualified device, which is available to order.

Data streaming company Confluent has announced the general availability (GA) of Tableflow, a solution designed to bridge operational and analytical data for real-time AI and next-generation applications. The announcement was made at Confluent’s data streaming event Current 2025 in Bengaluru. 

With Tableflow, data streaming in Confluent Cloud is now accessible in popular open table formats, unlocking advanced analytics and AI-driven decision-making.

A key highlight of the launch is the full production readiness of Apache Iceberg support, allowing Apache Kafka topics to be represented as Iceberg tables.

“At Confluent, we’re all about making your data work for you, whenever you need it and in whatever format is required,” said Shaun Clowes, chief product officer at Confluent. 

“With Tableflow, we’re bringing our expertise in connecting operational data to the analytical world. Now, data scientists and data engineers have access to a single, real-time source of truth across the enterprise, making it possible to build and scale the next generation of AI-driven applications.”

Moreover, Confluent has expanded its partnership with Databricks, introducing an early access program for Delta Lake, providing customers with a consistent real-time data view across operational and analytical applications.

Tableflow’s Key Enhancements

The latest update to Tableflow introduces several enhancements to improve AI-driven data access and management. With general availability for Apache Iceberg support, teams can now seamlessly convert Kafka topics into Iceberg tables, eliminating manual data transfers and enhancing AI scalability. 

The new Delta’s Lake early access program, developed in collaboration with Databricks, allows customers to use Delta Lake’s open-format storage layer, which processes over 10 exabytes of data daily, for real-time analytics. Furthermore, Tableflow now supports a Bring Your Own Storage (BYOS) model, giving users full control over data storage and compliance by allowing them to store Iceberg or Delta tables in their preferred storage buckets. 

To further streamline analytical workflows, Tableflow offers enhanced data governance through direct integrations with Amazon SageMaker Lakehouse via AWS Glue Data Catalog and Snowflake Open Catalog.

Tableflow has already drawn interest from enterprises using AI-driven analytics. Brady Perry, co-founder at Busie, noted, “Tableflow offers a promising path for our analytics engine to seamlessly consume operational data in Kafka in real time as Apache Iceberg tables, eliminating the need for additional preprocessing.”

Confluent has a number of partners across verticals, with prominent Indian players being Swiggy and Jio.  

IndiaAI Mission is set to collaborate with the Bill & Melinda Gates Foundation to develop AI-driven solutions aimed at transforming key sectors, Union Minister Ashwini Vaishnaw announced on X.

Vaishnaw confirmed that a Memorandum of Understanding (MoU) will soon be signed between the two entities. “AI solutions for better crops, stronger healthcare, smarter education & climate resilience— MoU soon between IndiaAI Mission & Bill Gates Foundation,” he stated following his meeting with Gates, who is currently in India.

#WATCH | Delhi | Former Microsoft CEO Bill Gates arrives in Parliament pic.twitter.com/rmTmBk423o

— ANI (@ANI) March 19, 2025

As part of its IndiaAI Mission, the government has recently launched AIKosha, a sovereign datasets platform, and an AI Compute Portal to enhance access to quality datasets and computational power. 

The initiative also includes plans to locally manufacture GPUs over the next three to five years under the ₹10,000 crore IndiaAI Mission.

The AI Compute Portal aims to provide subsidised GPU access for research and development, with approximately 14,000 GPUs already deployed and another 4,000 in the pipeline. 

The Ministry of Electronics and Information Technology (MeitY) had earlier initiated the procurement of 18,693 GPUs from shortlisted vendors.

Several ministries, including those handling agriculture, weather forecasting, and Bhashini, have already contributed datasets to the platform. Vaishnaw previously highlighted progress in developing India’s own AI foundational model, stating, “India’s own foundational model for AI is going well; we have 67 applications, 22 of which are for creating LLMs.”

Meanwhile, Bill Gates visited NITI Aayog’s Viksit Bharat Strategy Room (VBSR) on Monday, where he experienced an advanced AI-enabled immersive centre designed to enhance data-driven policymaking. The VBSR, launched on March 7, 2024, is a key initiative for evidence-based governance at the national level.

NVIDIA has announced two new personal AI supercomputers to handle AI workloads at the GPU Technology Conference (GTC) 2025 event. The company announced the DGX Spark and DGX Station, which are powered by the NVIDIA Grace Blackwell platform. 

These are aimed at helping AI developers, researchers, data scientists, and even students prototype, fine-tune, and infer from large language models on a desktop. Models can be run locally or deployed on any cloud-based platform. 

“DGX Spark and DGX Station bring the power of the Grace Blackwell architecture, previously only available in the data centre, to the desktop,” the company said. Original equipment manufacturer (OEM) partners like ASUS, Dell, HP and Lenovo are set to develop DGX Spark and the DGX Station. 

The DGX Spark, formerly known as ‘Project DIGITS’, is dubbed the world’s smallest AI supercomputer. It can deliver 1,000 trillion operations per second (TOPS) using AI models. It is priced at $3,000. The NVIDIA DGX Spark (5.91″ × 5.91″ × 1.99″) is only slightly larger than the Apple Mac Mini (5.00″ × 5.00″ × 1.96″).

On the other hand, the more powerful NVIDIA DGX Station features a massive 784 GB memory to accelerate AI workloads. It is also the first desktop system built with the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip. NVIDIA says the DGX Stations are purpose-built for teams who need the best desktop AI development platform. 

“This is the computer of the age of AI. This is what computers should look like,” said CEO Jensen Huang in the keynote. 

The company has opened reservations for DGX Spark Systems. The DGX Station is expected to be available later this year. 

Besides, NVIDIA had plenty of announcements to make at the GTC event. The company also partnered with General Motors (GM) to develop AI-powered self-driving cars and HALOS, a new AI-enabled automotive safety platform. Furthermore, NVIDIA also announced plenty of updates in the robotics sector. 

Earlier this year, the company unveiled the GeForce RTX 5090 GPU, which is 30% smaller in volume and 30% better at energy dissipation than the RTX 4090.

NASA astronauts Sunita Williams, Butch Wilmore, Nick Hague, and Russia’s state space corporation Roscosmos’ cosmonaut Aleksandr Gorbunov returned to Earth on March 19, splashing down in the Gulf of Mexico near Tallahassee in Florida. 

The crew landed at 3:27 am IST aboard a SpaceX Dragon spacecraft, ending a mission that lasted over nine months on the International Space Station (ISS). Their return followed the arrival of the Crew-10 mission, which docked on March 16 to replace them.

To celebrate the occasion, ISRO posted a welcome message from the chairman, V Narayanan, on X.

Welcome back, Sunita Williams!

Your safe return after an extended mission aboard the ISS is a remarkable achievement. A testament to NASA, SpaceX, and the USA’s commitment to space exploration! Your resilience and dedication continue to inspire space enthusiasts around the…

— ISRO (@isro) March 19, 2025

While he praised Williams’ resilience and noted India’s interest in utilising her expertise for future missions, her ancestral village, Jhulasan in Gujarat, celebrated with prayers and festivities.

Williams, who spent 286 days in space, smiled and waved upon exiting the spacecraft—a moment met with cheers from the recovery team. Hailing the return, the White House stated, “Promise made, promise kept.” 

NASA also broadcasted the return live, capturing the capsule’s fiery re-entry and a pod of dolphins near the landing site. The mission logged 4,576 Earth orbits and 195 million kilometres travelled.

The Mission Delays

The mission, originally planned for eight days starting June 5, 2024, was extended due to propulsion issues with Boeing’s Starliner spacecraft, which was deemed unfit for their return. It returned uncrewed in September 2024 after NASA and Crew-10’s launch, delayed by a ground support issue, finally enabled the handover. 

NASA shifted Williams and Wilmore to the Crew-9 mission, scheduling their homecoming with Hague and Gorbunov. The splashdown occurred at 5:57 pm ET on March 18, after a 17-hour journey from the ISS, where they undocked at 10:35 am IST on March 18.

We're getting our first look at #Crew9 since their return to Earth! Recovery teams will now help the crew out of Dragon, a standard process for all crew members after returning from long-duration missions. pic.twitter.com/yD2KVUHSuq

— NASA (@NASA) March 18, 2025

The astronauts emerged from the capsule in sequence, with Hague exiting first, followed by Gorbunov, Williams, and Wilmore. Recovery teams assisted them onto stretchers as a precaution due to their prolonged exposure to microgravity. 

They will now travel to Houston for a 45-day rehabilitation program to readjust to Earth’s gravity. “What a ride! I see a capsule full of friends here,” Hague said as communications resumed post-splashdown.

The crew still awaits health challenges, including muscle loss and vision issues from their time in space. The successful splashdown concluded a challenging chapter in NASA’s crew rotation efforts, spotlighting human endurance in space exploration.

Moreover, the capsule brought back time-sensitive research samples from the ISS, which will be offloaded and sent to labs for analysis. This will contribute to ongoing studies in biology, physics, and materials science.

Accenture expanded its AI Refinery, an industrial AI solution, and introduced a new AI agent builder on Tuesday. The new tool allows business users to build and customise AI agents without the need for coding, aimed at helping businesses adopt AI more quickly and easily. The AI Refinery platform and the new agent solutions are built using NVIDIA’s AI technology.

The company also announced that it is developing more than 50 industry-specific AI agent solutions and plans to reach 100 by the end of the year. These solutions are designed to streamline work and boost efficiency in industries such as telecommunications, financial services, insurance, manufacturing, healthcare, and retail. 

“We are seizing the significant opportunity to help our clients prioritise bold, high-impact initiatives that tackle core business challenges by reinventing processes end-to-end with generative AI and agentic technology,” said Lan Guan, chief AI officer at Accenture. 

Organisations like ESPN, HPE, Noli, and the United Nations are already exploring Accenture’s AI Refinery to improve their services.

At ESPN, Accenture is helping develop an AI-powered avatar called FACTS, which is being tested with Southeastern Conference (SEC) Nation to enhance the fan experience by providing sports data and insights in an easy-to-understand way.

HPE is working with Accenture to build a new AI solution that will help with category sourcing, spend management, and contract obligations. Noli, a beauty tech company supported by L’Oréal Group, has teamed up with Accenture to create a personalised beauty shopping platform. 

Meanwhile, United Nations is collaborating with Accenture to build a multilingual research agent. This AI tool will support over 150 languages and help people learn about the UN’s Sustainable Development Goals, encouraging awareness and participation.

Accenture’s industry agent solutions use NVIDIA’s advanced reasoning models. These AI agents can make better decisions and help human workers focus on more important tasks.

Furthermore, Accenture states that, as per the latest research, over one-third of organisations have already implemented industry-specific AI solutions for core processes like risk, claims, and underwriting. These organisations are three times more likely to see better-than-expected returns on investment.“Agentic AI is powering the next wave of AI, enabling enterprises to enhance productivity with intelligent agents capable of handling complex, multi-step challenges,” said Justin Boitano, vice president of enterprise software at NVIDIA.

The Lok Sabha Secretariat and the Ministry of Electronics and Information Technology (MeitY) have signed a Memorandum of Understanding (MoU) to develop Sansad Bhashini, AI-driven in-house solutions to streamline parliamentary operations in multilingual languages.

The signing took place in the presence of Lok Sabha Speaker Om Birla and Union Minister for MeitY Ashwini Vaishnaw, as reported by PTI.

Sansad will provide its corpus of legislative records for training and fine-tuning these AI solutions, while Bhashini will contribute translation capabilities and technical expertise.

संसद से जुड़े कार्यों का संचालन सुगम हो, माननीय सदस्यों को simultaneously यानि एक ही समय पर कई भाषाओं में कार्यवाही उपलब्ध हो सके, इसके लिए “संसद भाषिणी” पहल उपयोगी सिद्ध हो रही है।
आज केन्द्रीय इलेक्ट्रॉनिक्स एवं सूचना प्रौद्योगिकी मंत्री श्री @AshwiniVaishnaw जी की उपस्थिति में… pic.twitter.com/KPQUV2BpNW

— Om Birla (@ombirlakota) March 18, 2025

The initiative will integrate AI tools with parliamentary data, enabling seamless access to historical debates and legislative records in multiple languages. 

Parliamentary resources provided by Sansad will be used to train and fine-tune AI tools, while Bhashini will contribute translation capabilities and technical expertise.

As part of Sansad Bhashini, AI-powered solutions will include real-time translation of legacy debate documents, agenda files, and committee meetings into regional languages, ensuring greater accessibility. 

A smart chatbot for the Parliament website will assist members and officials in retrieving procedural rules and documents, offering instant, accurate responses and improving efficiency over time.

Additionally, an advanced speech-to-text system will transcribe parliamentary debates in real-time, reducing documentation challenges and ensuring easy reference. 

The initiative will also introduce speech-to-speech conversion with live translation, allowing immediate multilingual access to discussions and debates, along with automatic summarisation for faster decision-making.

Vaishnaw thanked Lok Sabha Speaker Shri Om Birla for his leadership, expressing confidence that Sansad Bhashini would revolutionise parliamentary processes through AI, enhancing multilingual accessibility and strengthening India’s tech-driven governance.

The signing ceremony was attended by Shri Utpal Kumar Singh, Secretary-General of Lok Sabha, and Shri Gaurav Goyal, Joint Secretary of the Lok Sabha Secretariat, who signed the MoU on behalf of the Secretariat.

In January, ahead of the Panchayat to Parliament 2.0 event, Om Birla conducted a live demonstration of the Sansad-Bhashini Speech-to-Speech translation system. The test, carried out in collaboration with the Bhashini team, included the participation of women representatives from Panchayats.

The government’s AI-powered language translation platform, Bhashini, is also translating the daily agenda papers of the Parliament into 10 regional languages. The team has already translated around 1,000 debates into Hindi and English by digitising 18,000 hours of speech data.

Amitabh Nag, the CEO of Bhashini, said in a post that this is the beginning of a historic co-creation journey with Indian Parliament for Sansad-Bhashini.

Apptronik, an AI-powered humanoid robotics startup based in the US, announced on Tuesday that it has raised an additional $53 million in its Series A round. 

This brings Apptronik’s total Series A funding to $403 million, adding to the previously announced $350 million, led by B Capital and Capital Factory, with participation from Google. 

New investors include Mercedes-Benz, Japan Post Capital, ARK Invest, Helium-3, Magnetar, RyderVentures, and a syndicate led by Korea Investment Partners.

The funding will support the production and deployment of Apptronik’s AI-powered humanoid robot, Apollo, across industries such as automotive, electronics manufacturing, logistics, and consumer packaged goods. 

Joerg Burzer, member of the board of management at Mercedes-Benz Group AG said, “Our work with Apptronik has given us a front-row seat to the incredible pace of progress in humanoid robotics and AI, and the transformative potential these technologies hold for modern manufacturing.”

Mercedes-Benz is using Apollo robots in its manufacturing process by employing a method, ‘teleoperation’, where the robots are initially controlled remotely by humans to learn specific tasks. 

Currently, the robots are being tested at Mercedes-Benz’s Digital Factory Campus in Marienfelde, Berlin, and in Kecskemet, Hungary, with plans to expand their deployment to additional sites, as announced by Burzer during a recent roundtable discussion in Berlin.

Apptronik aims to create a future where humanoid robots collaborate seamlessly with humans, initially in logistics and manufacturing, with future applications in healthcare and elder care. This investment follows a year of record growth for Apptronik, including the strategic partnership with Google DeepMind’s robotics team.

This month, Google Deepmind also introduced two new AI models, Gemini Robotics and Gemini Robotics-ER, which have been designed to enhance robotic capabilities in the physical world.

For this, the giant had expressed partnering further with Apptronik to develop the next generation of humanoid robots using these models. This will open the giant to more partnerships in the future, like those with testers including Agile Robots, Agility Robotics, Boston Dynamics and Enchanted Tools.

In February this year, Apptronik announced a partnership with Jabil, a global leader in engineering and manufacturing, to build and integrate Apollo humanoid robots into Jabil’s manufacturing operations. 

This partnership leveraged Apollo robots on the production lines that create them, marking progress towards robots constructing robots. The company had announced this in a post on X, saying it is “paving the way for Apollo to build Apollo.”

NVIDIA CEO Jensen Huang announced a collaboration with General Motors (GM) during his keynote speech on Tuesday at the NVIDIA GTC conference in San Jose. The partnership aims to use AI for next-generation vehicle experience and manufacturing.

GM will leverage NVIDIA’s accelerated computing platforms, including NVIDIA Omniverse with NVIDIA Cosmos, to optimise factory planning and robotics. 

Additionally, GM will use NVIDIA DRIVE AGX for in-vehicle systems to support advanced driver-assistance systems and enhanced safety features. This system will be capable of performing up to 1,000 trillion operations per second, facilitating the development of safe AVs at scale. 

The collaboration extends GM’s existing use of NVIDIA’s GPU platforms for AI model training across various operations. 

Mary Barra, chair and CEO at GM, noted, “AI not only optimises manufacturing processes and accelerates virtual testing but also helps us build smarter vehicles while empowering our workforce to focus on craftsmanship.” 

The partnership aims to create digital twins of assembly lines using NVIDIA Omniverse, allowing for virtual testing and production simulations to minimise downtime. GM will also train robotics platforms for material handling and precision welding to enhance manufacturing safety and efficiency. 

“The era of physical AI is here, and with GM, we’re transforming transportation, from vehicles to the factories where they’re made,” Huang said.

Also, a Safety System for AVs

In addition to this announcement, Huang also mentioned the importance of safety in Autonomous Vehicles (AVs) and launched NVIDIA Halos, a comprehensive safety system for AVs. 

Halos integrates NVIDIA’s automotive hardware and software safety solutions with AI research to ensure safe AV development from cloud to car. 

Halos operates on three levels: technology, development, and computation. The technology level includes platform, algorithmic, and ecosystem safety. The development level incorporates guardrails for design time, deployment time, and validation time.

Key elements of Halos focus on platform, algorithmic, and ecosystem safety. Halos complements existing safety practices and can potentially accelerate standardisation and regulatory compliance.