Siddharth Jindal

Article Complete Adobe Names Anil Chakravarthy as CEO, Shantanu Narayen to Become Executive Chair The leadership change comes as Adobe expands its focus on agentic software across creativity, productivity and customer experience. SEPTEMBER 4, 2026, 9:17 AM 5 min Chakravarthy, who currently leads Adobe's Customer Experience Orchestration business and worldwide field operations, will also join Adobe's Board of Directors when he becomes CEO. “I could not be more confident that Anil is the right person to lead Adobe's growth in an AI-driven era and look forward to working closely with him in my new role as executive chair,” Narayen said in a statement Chakravarthy said he would focus on growth and Adobe's position in agentic software across creativity, productivity and customer experience. “I am deeply honoured to have been chosen to lead Adobe during this pivotal moment,” Chakravarthy said. “I'm energised by the opportunity to fuel growth and drive Adobe's leadership in the next era of agentic software for creativity, productivity and customer experience.” Chakravarthy joined Adobe in January 2020 as Executive Vice President and General Manager of its Digital Experience business. Later that year, he also took responsibility for worldwide field operations serving enterprise customers across Adobe's product portfolio. He became president of Digital Experience and worldwide field operations in December 2021. During his tenure, Chakravarthy led Adobe's expansion in Customer Experience Orchestration, including the development of products such as Adobe CX Enterprise, GenStudio and Brand Visibility. He also oversaw the scaling of Adobe Experience Platform and the introduction of CX Enterprise Coworker. Chakravarthy was also involved in Adobe's acquisitions and integration of Workfront and Semrush. Before joining Adobe, Chakravarthy served as CEO of Informatica for four years. He joined the company in 2013 as an executive vice president and previously held executive roles at Symantec and VeriSign, along with a role at McKinsey & Company. Chakravarthy holds a Bachelor of Technology in Computer Science and Engineering from the Institute of Technology, Varanasi, and a master's degree and PhD from the Massachusetts Institute of Technology. Narayen has led Adobe since December 2007, overseeing the company's shift toward a subscription-based business model and its expansion into digital experience and AI-powered products. As Executive Chair, he will continue working with the company and Chakravarthy after the transition. Article Bottom · 728×90 Advertise Here Your reaction Discussion What's your take on this story? Start with a thought Siddharth Jindal Tech Journalist Siddharth is a media graduate who loves to explore tech through journalism and putting forward ideas worth pondering about in the era of artificial intelligence. Got a tip? Share confidential information with AIM. Wake up informed Make sense of the day's AI news and breakthroughs with our morning briefing. Industry intelligence Receive a roundup of AI adoption stories by industry vertical, curated for professionals. By signing up, you agree to our Privacy Policy OpenAI Declares ‘AGI Era' after Launching GPT 6 The company believes that it is the best model in the world for professional work. SEPTEMBER 4, 2026, 8:50 AM 5 min Article Bottom · 728×90 Advertise Here Your reaction Discussion What's your take on this story? Start with a thought

The models will be offered as Digital Public Goods, with open weights and sovereign APIs that let developers build applications without training language models from scratch.

The new infrastructure will support post-flight inspection, requalification and faster production of critical launch vehicle components. No country can realistically ensure complete sovereignty across all the layers of AI.

The company said the funding will expand its frontier AI research, increase compute capacity to train models, scale infrastructure, and support its commercial growth and international expansion.

AlphaGenome Atlas helps scientists prioritise variants, investigate their molecular effects, and uncover genetic links to rare diseases and common traits.

Article Complete Accenture and Google Cloud's partnership will create a 1,000-person forward engineering workforce. Google DeepMind's New Tool Maps All 9 Bn DNA Mutations in Humans AlphaGenome Atlas helps scientists prioritise variants, investigate their molecular effects, and uncover genetic links to rare diseases and common traits. SEPTEMBER 9, 2026, 9:33 AM 5 min Article Bottom · 728×90 Advertise Here Your reaction Discussion What's your take on this story? Start with a thought RB RNK BAMEZAI 23m ago

Meta says Muse uses a dedicated virtual machine and a separate Sentinel system to control internet access, credentials, and sensitive actions.

The model is designed to handle code-mixed speech, financial terminology, telephony noise, and low-bandwidth calls with low latency.

Article Complete Mahindra Finance, Sarvam Scale Voice AI to Over 1 Cr Calls The deployment now covers customer outreach, collections, and field-level employee feedback across 12 Indian languages. SEPTEMBER 10, 2026, 3:51 PM 5 min Mahindra Finance has used voice agents developed by Mahindra AI on Sarvam's platform to make more than 1 crore calls to customers. The agents operate across 12 Indian languages and are being used across the company's rural and semi-urban markets. In sales, the voice agents engage with customers and identify potential cross-sell opportunities across vehicle, tractor, SME, housing, insurance, and investment products. In collections, they support conversations ranging from pre-due reminders to write-off and repossession stages. The partnership also covers employee engagement. Voice agents collect feedback from field teams, giving Mahindra Finance's leadership access to frontline operational insights. Mahindra AI has combined the voice agents with in-house machine learning models to run sales and collections campaigns. The models identify customers and opportunities, while the voice agents use those insights to conduct conversations in the customer's preferred language. Each call is recorded and analysed through AI pipelines. The resulting information is connected to systems including CRM, loan servicing, and collections, allowing the company to use insights from conversations in subsequent business processes. “Our customers have always trusted us to stay close to them, whether they are in a city or a village. Voice AI has allowed us to extend that closeness at scale, reaching people proactively, in their own language,” said Raul Rebello, Managing Director and CEO, Mahindra Finance, in a statement. “As we diversify into new lines of business, this partnership with Sarvam is central to how we scale customer-first financial services across Bharat,” he added. Pratyush Kumar, Co-founder, Sarvam, said the deployment shows how voice AI can be integrated into financial services operations. “Mahindra Finance has set a strong benchmark for what AI at scale can look like in financial services,” he said. “More than 1 crore calls across sales, collections and employee engagement show what becomes possible when AI is deeply embedded into the business and continuously learns from customer outcomes.” Article Bottom · 728×90 Advertise Here Your reaction Discussion What's your take on this story? Start with a thought Our Coverage of AI News • DeepSeek says the new model improves coding and agentic workloads while giving users control over its reasoning effort. Read more → • The model is designed to handle code-mixed speech, financial terminology, telephony noise, and low-bandwidth calls with... Read more → • Swiggy's data-processing pipeline, which previously took about six hours, now delivers insights in near real-time. Read more → • Open models add an important dimension to that strategy because they allow enterprises to shape AI around their own... Read more → Siddharth Jindal Tech Journalist Followed by 29 readers Siddharth is a media graduate who loves to explore tech through journalism and putting forward ideas worth pondering about in the era of artificial intelligence. Got a tip? Share confidential information with AIM. Wake up informed Make sense of the day's AI news and breakthroughs with our morning briefing. Industry intelligence Receive a roundup of AI adoption stories by industry vertical, curated for professionals. By signing up, you agree to our Privacy Policy Deloitte Launches Open Model Engineering Practice in India to Scale Agentic AI Open models add an important dimension to that strategy because they allow enterprises to shape AI around their own data, processes, and context SEPTEMBER 10, 2026, 3:51 PM 5 min The practice will initially operate across North America, Europe, and Asia-Pacific, including India, and will focus on enterprise AI applications built on open-source AI frameworks and open models. Deloitte said the initiative aims to give enterprises greater flexibility over model selection, costs, deployment environments, data, intellectual property, and model behaviour as AI adoption expands. “Open models add an important dimension to that strategy because they allow enterprises to shape AI around their own data, processes and context rather than designing the enterprise around the limitations of a model. Our Open Model Engineering practice is designed to build that flexibility in from the start, without compromising governance or the distinctiveness of the business,” said Sathish Gopalaiah, President, Consulting, Deloitte South Asia, in a statement. According to Deloitte, enterprises are increasingly weighing four factors when deploying AI: flexibility to select models and architectures for different workloads, predictable costs as aAgentic AI usage grows, sovereignty over where models are deployed, and greater control over enterprise data, IP, and model behaviour. The consulting firm said tThe new practice will help clients evaluate proprietary and open models, aAgentic AI platforms, cloud services, and on-premises infrastructure based on individual workloads. It will also focus on managing token economics, fine-tuning open models for geographical, linguistic, and cultural contexts, and giving enterprises greater control over where models run and what data they share. Deloitte's initial Open Model Engineering work will focus on enterprise applications powered by NVIDIA Nemotron open models and NIM microservices. Deloitte firms will also help clients develop sovereign AI stacks using open-source frameworks, fine-tune open models, and strengthen cybersecurity using open-source security tools. “Enterprises need both open and proprietary models for different workloads,” said Kari Briski, VP of Generative AI at NVIDIA. “Deloitte's Open Model Engineering practice, built on NVIDIA Nemotron models, gives developers greater control over enterprise data and proprietary information while enabling secure, responsible deployment of agentic AI.” The practice will also leverage Deloitte's Zora AI digital workforce platform, with agentic harness capabilities built on NVIDIA Nemotron models and NIM. The platform intends to allow enterprises to deploy, optimise, and govern AI agents using open models within their own environments. Deloitte plans to hire, train and certify forward-deployed engineers globally through fiscal year 2027. These engineers will work directly with clients to implement open-model solutions and are expected to form the operational backbone of the new practice. Article Bottom · 728×90 Advertise Here Your reaction Discussion What's your take on this story? Start with a thought Shalini Mondal Senior Tech Journalist Followed by 35 readers Shalini is a senior tech journalist, exploring the latest advancements in AI and GCC sector. When she's not reporting on the latest innovations, you can find her immersed in her next literary adventure. Got a tip? Share confidential information with AIM.

Article Complete Karnataka Approves ₹35 Cr AI Hub at IIIT Bangalore The initiative will combine industry-linked certification, startup incubation and AI research through an integrated platform with real-world testbeds. Shopify Ditches React Native, Moves Shop App to Kotlin & Swift The decision has drawn reactions from React Native developers, who questioned the performance comparisons and whether coding agents alone justify maintaining separate native codebases. SEPTEMBER 11, 2026, 4:17 PM 5 min With AI assistance, the company said it took a proof of concept to a rebuilt native app published in the App Store in just 12 weeks. This reverses the company's 2020 decision to move to React Native. “That decision has served the Shop app well, but our increasing ability to develop with coding agents has allowed Shop to go fully native, building with Swift and Kotlin,” said the company. Shopify said that advances in coding agents changed the tradeoffs behind maintaining a shared mobile codebase. Using Swift and Kotlin means that the company needs to build separately for iOS and Android, “but agents made it reasonable to reconsider that decision”, said the company. Agents can now handle enough implementation, translation, testing and review work that the duplication is no longer the deciding factor it once was. With this new native architecture, Shopify said that startup time for the Shop app was reduced by 23% for iOS and 50% on Android. Session stability rose from more than 99.5% to more than 99.95%, which Shopify described as a tenfold reduction in crashing sessions. The Android release build also shrank by 109 MB, or 37.2%, while iOS app size increased by 1 MB. Shopify said the migration preserved sign-in sessions, push notifications and analytics events required by downstream systems. It also retired some screens and streamlined others. The company is using a workflow called Helix to migrate its wider app portfolio. Helix breaks screens into reviewable checkpoints, requiring tests, visual comparisons, adversarial code reviews and human approval before implementation proceeds. Shopify is also developing a command-line interface that lets agents inspect app state and execute actions without relying on slow simulator interactions. The Shopify app, which has more than 300 screens and includes widgets, an Apple Watch app and Siri Shortcuts, is now being migrated and is expected to ship later this year. Shopify said its other mobile apps will follow. Shopify will continue sponsoring React Native Skia through the end of 2026, while FlashList will receive critical compatibility fixes as the company discusses long-term stewardship. Restyle will be archived after the end of 2026. However, the reaction to Shopify's decision has focused on whether coding agents have changed React Native's engineering trade-offs, or simply made it cheaper to move away from the framework. One software developer wrote on X that Shopify's explanation was “very thin on the reasoning as to why”, arguing that the post focused on LLMs making native development easier without identifying a specific React Native limitation that had prompted the migration. The decision, he suggested, appeared to be motivated primarily by reducing abstraction. Jamon Holmgren, CEO of React Native consultancy Infinite Red, added some context on X about the performance comparison. He noted that the Shop app had not yet migrated to React Native's New Architecture, which was developed in part to address startup-time issues. “The one thing that was almost certain to improve startup time hadn't happened yet,” Holmgren said, questioning how much of the reported performance improvement could be attributed to moving away from React Native rather than completing that transition. Alex Mikucki, a software developer, wrote on X that Shopify's rapid rewrite was unsurprising, arguing that declarative UI frameworks such as SwiftUI and Jetpack Compose are similar enough for agents to migrate between them effectively. His experience rebuilding Expo Go's UI in Jetpack Compose reinforced that view. The harder challenge, he said, is maintaining consistent business logic and behaviour across separate native codebases. Agents cannot necessarily resolve the trade-off between cross-platform consistency and platform-specific feel. “I don't think react-native will go away, but I definitely feel react-native is evolving, will evolve further.” He predicted more native components for performance-sensitive interfaces, greater use of over-the-air updates, and architectures that combine native and JavaScript components. “I don't think the falling cost of writing lower level code makes abstractions automatically obsolete,” he wrote. “You get for free a lot of community effort on deciding/mapping platform quirks, stuff that would cost tokens and engineering effort otherwise, or even worse, would be missed and be a long-running paper-cut in your app.” Article Bottom · 728×90 Advertise Here Your reaction Discussion What's your take on this story? Start with a thought About the Author Supreeth Koundinya Contributor Followed by 13 readers Got a tip? Share confidential information with AIM. Subscribe to notifications