Год: 2025

AI is the new digital, Accenture says in its latest Technology Vision 2025 report. This 25th edition of the company’s research, titled “AI: A Declaration of Autonomy,” frames AI as not only a pivotal technology but also a catalyst for entirely reshaping workflows and business processes.

AI will permeate every part of the enterprise, with its transformative impacts already becoming evident in industries and government operations, according to the report's author Karthik Narain, Accenture group chief executive of technology and CTO, and his team of editors and researchers.

“Advancements in digitizing knowledge, new AI models, agentic AI systems, and architecture enable enterprises to create their own unique cognitive digital brains,” Narain said in a release. “While conventional technologies have long supported pre-determined business needs, this is a generational moment of transition. The autonomy created by these generalized AI systems can help organizations be more dynamic and intention-driven than ever. It will allow leaders to rethink how digital systems are designed, how people work, and reinvent how they create products and interact with customers. But trust underpins it all, as systems will only ever be as autonomous as they are trustworthy.”

AI Agents and the ‘Binary Big Bang’

Accenture says we have reached the "Binary Big Bang": Organizations are entering a transformative era where foundation models are revamping technology systems and how they’re designed, used, and managed.

“Today’s technologies are not the endgame—they are how we are getting there. A technological future of abundance, abstraction, and autonomy is what leaders need to be planning for,” the report notes.

Autonomy is the keyword here. In recent months, predictions about AI agents (autonomous systems designed to perform specific tasks) have dominated conversations in the tech world, fueled by the rapid adoption of generative AI.

Accenture says enterprises are beginning to embrace AI agents, noting that 77% of executives agree AI agents will reinvent how their organization builds digital systems. Additionally, 48% of executives say AI agents would improve flexibility of their organization’s digital architecture, the report says. AI agents could massively change how we interact with technology: 78% of executives agree that digital ecosystems will need to be built for AI agents as much as for humans over the next 3-5 years.

Autonomy comes with responsibility, of course, and trust is going to play a huge part in how independent these systems can actually become. Accenture says to harness the power of autonomous systems, companies must implement robust monitoring and strategic training involving safeguards like tracking data access and monitoring output quality to establish clear governance and build employee trust.

A Personalized (and Personified) Approach

The report also investigates how businesses can maintain their brand identity when adopting AI agents to ensure AI enhances rather than dilutes the brand. Generic AI agents risk creating bland, impersonal interactions, with the report noting that 80% of executives agree that chatbots that all sound the same are creating differentiation challenges for organizations like theirs.

Source: Accenture

To solve this, personified AI offers a way to infuse agents with brand-aligned personality and values. Enterprises are embracing training techniques that specify the words or phrases a model uses, how it structures sentences, or its speech patterns and tone, the report notes.

“Personified AI might just seem like an interesting exercise in how models present themselves, but it will be a core differentiator for businesses in the future—both in how customers will interact with the business on their channels and how businesses will be represented by agents in other AI applications,” the report says.

These agents can build trust by personalizing interactions, fostering meaningful relationships, and managing large-scale customer engagement autonomously, but the report cautions that their success will depend on intentional implementation.

This is top of mind for many, as 95% of executives report establishing or maintaining a consistent personality will be important or very important to their customer-facing AI agents over the next 3 years.

From Code to Kinetics: Giving LLMs a Body

Another topic covered by the research is how machine intelligence is moving into the physical world, with the robotics industry entering a watershed era driven by foundation models. Once limited to repetitive tasks and rigid programming, robots are now becoming dynamic systems capable of reasoning, understanding their surroundings, and responding intelligently to complex instructions, Accenture states.

This evolution, powered by innovations in large language models, vision-language models, and robotics foundation models, is enabling robots to achieve greater autonomy and versatility while broadening their potential applications across industries.

Source: Accenture

The integration of foundation models is removing long-standing barriers, allowing robots to operate effectively in diverse and unpredictable environments. Tasks that once required extensive programming, such as retrieving a specific item based on a spoken request, are now achievable through more intuitive interactions.

This shift is making robotics accessible to broader use cases, the report asserts, moving robots from specialized industrial settings into roles that directly interact with people and address everyday challenges. Successful interaction with people will be key, and 80% of executives believe natural language communication will increase trust and collaboration between humans and robots.

The report also explores how robotics hardware is advancing to match the versatility of the software. While internal components are increasingly customized for efficiency, overall designs are leaning toward general-purpose configurations, such as humanoid forms that can navigate human-centric spaces with ease. These innovations are opening up opportunities for businesses to streamline workflows and explore applications that were previously impractical or impossible.

Again, responsibility will be essential, with 75% of executives agreeing that organizations will need to factor in the dimensions of responsible AI principles as robots get deployed into physical settings.

From Automation to Autonomy

Finally, even as leaders across industries are racing to capitalize on the transformative potential of AI, concerns about its impact on jobs and employee trust are slowing adoption.

Accenture says the key to overcoming this barrier lies in making generative AI accessible and empowering employees to use it creatively. Unlike traditional top-down approaches to automation, generative AI enables a collaborative dynamic where workers can take the lead in designing solutions and driving innovation. By shifting from a focus on automation to fostering autonomy, businesses can unlock new skills, boost engagement, and spark innovation at every level, the company says. For example, a marketer might use AI-driven data analysis to test a new idea, or a truck driver could prototype an app to streamline inventory processes.

Source: Accenture

This bottom-up approach will not only enhance workflows but also create a culture of innovation where every employee becomes a contributor to growth, Accenture claims. By trusting employees to take the creative reins, businesses can ensure that AI becomes a tool for empowerment rather than a source of uncertainty.

Enterprises are optimistic: 95% of executives expect the tasks their employees perform will moderately or significantly shift to innovation over the next 3 years given the influx of automation enabled by AI. But there is also the dreaded skills gap to tackle, with 68% of executives reporting a need to upskill/reskill their employees in AI tools and technologies, within the next 3 years.

The company says input for the 2025 report was gathered from an external advisory board of more than two dozen experts spanning academia, business, and the public sector. Primary global research included two parallel surveys: more than 4,000 executives across 21 industries and 28 countries, and more than 12,000 consumers fielded from Oct. to Dec. 2024.

"Our 25th Technology Vision gives leaders a look into what’s ahead when AI continuously learns, acts autonomously with and on behalf of people, and pushes enterprises and the people who use it into new and exciting ways to continuously reinvent," said Julie Sweet, Accenture chair and CEO. “But unlocking the benefits of AI will only be possible if leaders seize the opportunity to inject and develop trust in its performance and outcomes in a systematic manner so businesses and people can unlock AI’s incredible possibilities."

These ideas show how the future of AI will not only be reliant on the technology behind it but will embody a complete reimagining of how people and machines can work together to shape a smarter, more dynamic world. Read the full report at this link.

After debunking myths about Bengaluru’s infamous traffic, Joint Commissioner of Police (Traffic), MN Anucheth, shared his belief that self driving vehicles and Level 5 autonomous cars could navigate the city’s chaotic roads—but he questioned whether there’s a real need for such technology in Namma Bengaluru.
Bengaluru Traffic Commissioner said that while fully autonomous (Level 5) vehicles could theoretically navigate the city’s chaotic roads, their practicality and adoption remain uncertain.

“If a Level 5 vehicle is equipped with sufficient inputs like radar, LiDAR, and computer vision, it could learn both good and bad behaviours to navigate through our roads,” he noted. However, he questioned the necessity of such advanced vehicles in India’s context, adding, “Would you spend so much for a Level 5 vehicle when hiring a driver is easier and more cost-effective here?”

Given the safety concerns and the rise in road rage incidents in the city, the case for self-driving vehicles and robotaxis such as Tesla and Waymo becomes increasingly compelling.

As Bengaluru’s Metro and suburban rail networks expand, the city’s focus appears to be on improving public transportation. For now, the dream of fully autonomous vehicles navigating Namma Bengaluru’s roads remains more of a futuristic vision than an immediate reality.

Citing the USA and Canada, where the shortage of drivers for heavy goods vehicles, such as long trailers and trucks, has accelerated the push for Level 4 and Level 5 automation, in regions where there is no shortage of the same, investing in Level 5 autonomous vehicles might not be justifiable.

“I don’t think the adoption will be that much because one, it’s very cost prohibitive. Second, I think, it’s easier to hire a driver and have a level 3 which is a driver assistant, giving more importance to road safety rather than automation,” he said.

While emphasis lies on four-wheelers, Anucheth also believes that if two wheelers have better adoption of tech, accident deaths can significantly come down. “If you look at the vulnerable group in Bengaluru city, about 72% are two-wheelers,” he said, attributing 2-wheelers as the cause of maximum accidents.

Autonomous Vehicles on the Rise

Recently, at CES 2025, NVIDIA chief Jensen Huang said, “I predict
that this [autonomous vehicles] will likely be the first multi-trillion dollar robotics industry.”

At the same event, NVIDIA released Cosmos, a platform built to accelerate the development of autonomous vehicles and robots. The platform consists of work foundation models (WFMs), video tokenisers, guardrails and other features that will help developers build models without the dependency of real-world data.

Tesla, NVIDIA are all heavily investing in autonomous vehicle production and abilities. Tesla’s fully autonomous robotaxi is being positioned as a safety vehicle, allowing one to travel without the risk of any form of accidents or mishaps.

Not just vehicular safety, but passenger safety is also becoming a rising concern. Recently, a woman passenger jumped out of a moving autorickshaw run by a when she sensed the driver was taking a deviated path. With robotaxis, safety can be easily met. Something Musk had positioned as the predominant goal for his vehicles.

Interestingly, Indian players are also working on fully autonomous vehicles, with some claiming level 5 autonomy. AI and robotics startup Swaayatt Robots is building level 5 autonomy and has raised $7 million at a valuation of $175 million. Similarly, Kochi-based Rosh AI has been testing their fully autonomous vehicles for more than a decade.

The post Traffic Commissioner Says Fully Autonomous Cars Are Possible in Namma Bengaluru appeared first on Analytics India Magazine.

Salesforce India chief Arundhati Bhattacharya, on the sidelines of AI Pitchfield, told AIM that the company witnessed a growing adoption of agentic AI in India during a recent event. “India’s startup ecosystem, being the third largest in the world, is uniquely positioned to address challenges at a billion-plus scale. The progress we’re seeing with agentic AI is phenomenal, even though companies are just starting to dip their toes into it,” she remarked.

AI Pitchfield is a new startup pitch competition hosted by Salesforce Startup Community, in collaboration with Salesforce Ventures, Lightspeed India and Khaitan.

Salesforce Ventures, which has committed $1 billion globally to AI startups, sees immense potential in India as it embraces agentic AI for diverse use cases. Bhattacharya emphasised the importance of prerequisites such as clear data strategies and robust security frameworks before fully integrating AI agents. “Companies here are proactive, but they’re taking time to align their business needs with the right data sources and compliance measures,” she noted.

With pilots already underway with major Indian enterprises, Salesforce Ventures is optimistic about India’s ability to innovate in agentic AI, paving the way for future-ready solutions at scale.

Bhattacharya said that the company is running pilot programs with a significant number of companies in India using Agentforce 2.0, without delving too much into the numbers.

“It’s been very good, the kind of reactions we have got,” she said. “We are running pilots with a very large number of companies. The fact remains that it’s been very exciting.”

Introduced last year in September, Agentforce 2.0 introduces a vast library of pre-built skills that facilitate rapid customisation and deployment of AI agents. These skills cover various functionalities across Salesforce CRM, Slack, Tableau, and partner applications via AppExchange.

Reflecting on the progress since the launch, Bhattacharya said, “We are just three or four months out from there, and the progress is phenomenal. I am really enthused about it.”

However, she noted that while conversations with customers are advancing, the announcement of major deals will take time. “That will be a little more in the future. People are just now dipping their toes into it and experiencing.”

According to Bhattacharya, companies must take key preparatory steps before deploying AI agents: “First and foremost, you have to determine the use cases. Where do you really want to use them? What are the pain points you want to resolve?”

Security and compliance are key concerns for companies considering AI adoption. Bhattacharya acknowledged these apprehensions, saying, “People do want to understand what are the securities, whether they are compliant, whether they are secure. There is a lot of concern on that, where AI is concerned.”

Addressing the broader industry discussions around generative AI, she said, “If you look at ChatGPT, there has been a lot of talk about how secure it is, whether my data is going out in order to train the model. So there are a lot of questions that the companies are asking, which we need to answer to their satisfaction.”

She reiterated the importance of companies having a clear business strategy and a well-organised data strategy as prerequisites for adopting AI agents. “Once these two are there, these are prerequisites, then the agents come into post,” Bhattacharya said.

Agentic War Begins: Microsoft vs Salesforce

Microsoft chief Satya Nadella, in a recent podcast, indirectly took a dig at the company, by saying that traditional SaaS companies will collapse in the AI agent era. “I think the notion that business applications exist—that’s probably where they’ll all collapse, right, in the agent era. Because if you think about it, right, they are essentially CRUD databases with a bunch of business logic,” he said.

“Business logic is all going to these agents, and these agents are going to be multi-repo CRUD. They’re not going to discriminate between what the back end is; they’re going to update multiple databases, and all the logic will be in the AI tier,” he added.

At the Microsoft AI Tour in Bengaluru, Nadella said that “building agents should be as simple as creating a spreadsheet”. He introduced a no-code platform called Copilot Studio that allows users to create new agents based on their needs.

“Think of AI as a co-pilot for your work. It’s the UI for AI,” Nadella said, illustrating the role it will play as an interface between employees and the AI. He gave the example of an AI agent in a healthcare setting, describing a scenario where a doctor prepares for a tumour board meeting, and the AI creates the agenda, prioritises cases, and takes detailed notes during the discussion.

The post ‘Indian Startups Will Define the Future of Agentic AI,’ Says Salesforce India CEO appeared first on Analytics India Magazine.

Elon Musk, the founder and CEO of xAI, said that the company’s Grok-3 model has finished pre-training and confirmed that the model will be launched in the next 3-4 weeks.

However, the model is said to have used 10 times more compute than its predecessor, Grok-2. This is quite a bold move in an era when experts suggest that LLM scaling may have hit a wall and that additional computing while training the model will only yield diminishing returns.

Grok-3 will train on NVIDIA’s H100 GPUs – 100,000 of them. It has been trained on Colossus, which xAI claims is the world’s most powerful AI training system. He also said the cluster was built in 122 days from start to finish.

Moreover, this is the first time a cluster of this size has been built. “Grok 3 will resolve the question of whether or not we’re hitting a wall,” Gavin Baker, CIO and managing partner at Atreides Management, said on X.

Naturally, it consumes a mammoth amount of power. Yann Le Du, a physicist, calculated that training with 100k H100 GPUs is equivalent to the power consumed by 7% of a typical nuclear reactor. For a month, this consumes ~181 trillion joules of energy, which is ~10,000 times the energy consumed by a human brain over 30 years (~19 billion J at ~20W).
“Is Grok’s capacity comparable to that?” he asked. That is what everyone wants to know – will the model outperform its competitors?

So What is Musk’s Plan?

Recently, former OpenAI chief scientist Ilya Sutskever said that pre-training with more datasets might soon be over, as they are comparable to fossil fuels and may soon be exhausted. Synthetic data could be an answer to that, he said.

One of Musk’s comments earlier on an X Spaces conversation echoes this sentiment. “You really have started running into this data problem where you have to either create synthetic data or use real-world videos,” he said.
“Those are the two sources of unlimited data – synthetic data and real-world videos. Tesla has a pretty big advantage in real-world video,” he added.

Musk also revealed that the model will launch in Tesla’s vehicles soon.

Another user on X said that Grok-3 is rumoured to be the ‘most powerful base model in existence’. Unlike OpenAI’s approach to scaling laws, it won’t use test-time computing for reasoning. “I expect Grok 3 to be a failure. Test time scaling effectively enlarges the model by a factor of 1000-10000. If they can’t do it at xAI, they have just burnt a lot of money,” said a user on X.

So, is the company relying purely on a brute-force compute scaling approach?

AIM reached out to a few experts in the AI industry to understand what Grok-3 is possibly trying to do and what it may achieve. The model may be using 10 times more compute power to train, but will it achieve performance gains that are directly proportional?

Paras Chopra, an AI researcher and founder of Turing’s Dream, said, “Performance is often log-linear. So I’d say 10x more compute would have a ~double jump in performance over Grok 2.”
We also reached out to Sudipta Biswas, who has built an architecture to enhance an AI model’s ability to interact with external data sources. He suspects that Grok-3’s architecture may be noticeably different from Grok-2’s. “Hence, pretraining is required from zero,” he said.

He also suggested that Musk might be using excess computing for parallelised training: “If you are using 10x more compute, you can complete pretraining in 10x less time.”

However, despite using unprecedented computing power, Musk has failed to realise his hopes of delivering the model early enough. He previously stated that he planned to reveal it in December last year, but it has yet to materialise.

However, if the model arrives by next month, it will settle some of the most heated debates in the AI ecosystem.

The Tale of Two Models

Speaking of models pre-training on mammoth computing, China’s DeepSeek-V3 is unmissable because its approach starkly contrasts with Grok-3’s. In an earlier interview, Musk revealed that Grok-3 would finish training in three to four months, which is 100,000 GPUs x 2,880 hours. xAI used at least 200M GPU hours for training.

In contrast, the DeepSeek-V3 was trained on just 2.788 million NVIDIA H800 GPU hours. On most benchmarks, the model outperformed Meta’s 405 billion parameter Llama 3.1 and even closed-source Claude 3.5 Sonnet and GPT-4o in several tests. The model is a testament to achieving superior performance without using excess computational resources.

However, xAI is not alone. Meta revealed that its upcoming Llama 4 is being trained on a similar cluster size. “[This is] bigger than anything that I’ve seen reported for what others are doing,” said Meta chief Mark Zuckerberg in the company’s earnings report released in October.

“By the way, you can do some pretty neat reasoning stuff with a 200k GPU cluster,” said Erik Zelikman, a member of xAI’s technical team.

Again, the general concern is that these models better not waste computing power.

“It would be [kind of] sad if Grok 3 used 20x compute of Grok 2 and was still mid [mediocre]. I really hope they spend time on fixing their pipeline too, and not just GPUs,” said a user on X. However, if the company is innovating at the architectural level, like DeepSeek, and is using a 100K GPU cluster – it would yield unimaginable results.

But how close will the model get to OpenAI’s most powerful o3 model? We’ll soon know.

That said, even before delivering Grok-3, Musk revealed that Grok-4 would be released later this year and Grok-5 the next year. Moreover, the company is also hinting at building a reasoning model, as it’s looking to hire AI engineers and researchers.

The post Elon Musk is Using 100,000 GPUs for Grok-3 – But Why? appeared first on Analytics India Magazine.

Eric Schmidt, former CEO of Google, has reportedly invested in Relativity Space Inc., a California-based company specialising in 3D-printed rockets, according to Bloomberg sources familiar with the matter.

Founded in 2015, Relativity Space was once valued at $4.2 billion and has attracted prominent investors, including Fidelity Management, Mark Cuban, and actor Jared Leto.

While the exact amount of his investment remains undisclosed, his involvement comes at a critical time for the company, which struggled to secure funding last year, as reported by Bloomberg. Neither Schmidt’s representative nor Relativity have announced the specifics of the deal.

About the Rockets

The company launched its first 3D-printed rocket, Terran 1, in March 2023, though it failed to reach orbit during its test flight. Terran 1 was not only the largest 3D-printed object ever created (110 feet tall and 7.5 feet wide) but also the first to attempt an orbital flight.

Comprising 85% 3D-printed material by mass, the rocket was powered by nine Aeon 1 engines on its first stage and a single Aeon Vac engine on its second stage. It utilised liquid oxygen (LOX) and liquid natural gas (LNG) as propellants, chosen for their efficiency and potential for high-rate reusability.

Subsequently, the startup shifted its focus to developing a larger rocket, the Terran R, slated for its maiden flight in 2026.

Terran R is a 270-foot-tall, two-stage rocket with an 18-foot diameter and a 5-meter payload fairing, engineered to cater to commercial and government needs for delivering payloads to Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and Geosynchronous Orbit (GEO).

Prioritising first-stage reusability, Terran R can carry 23,500 kg to LEO with downrange landing, 5,500 kg to Geosynchronous Transfer Orbit (GTO) with downrange landing, and up to 33,500 kg to LEO in an expendable configuration.

Its architecture includes a high angle of attack reentry to minimise propellant use, an aerodynamic design for improved reentry stability, and a lightweight, passively actuated landing leg system for rapid reuse.

Additionally, a heat shield on the aft end is optimised for frequent reusability, reinforcing Terran R’s focus on efficiency and operability in the growing space launch market.

Previously…

In 2024, Relativity faced financial difficulties, with dwindling reserves and challenges raising funds for the Terran R’s development and operations. Despite these hurdles, the company stated it is “fully committed” to its ambitious 2026 launch target and continues to partner with “strong capital partners” who share its vision.

Last year, the company also announced the appointment of Umer Khan as chief information officer and senior VP of software. In his role, Khan oversees software engineering for rocket design, launch, and mission control, as well as technology infrastructure, including AI, cybersecurity, and factory automation.

He brings over 25 years of experience, including leadership roles at SpaceX and MaxLinear, where he scaled IT systems and supported critical aerospace operations.

As for Schmidt, who stepped down from Google’s board in 2019, he has since focused on investment, philanthropy, and advisory roles, including work with the U.S. government and his family foundation. He has also been recently famous for co-authoring the book ‘Genesis: Artificial Intelligence, Hope and the Human Spirit’.

His support will be seen as a notable boost for Relativity Space as it aims to redefine space exploration with its pioneering 3D-printing technology.

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