Cisco aims to build AI-ready data centres, future-proof workspaces: Chuck Robbins
Live Events
Networking hardware and security solutions provider Cisco said Tuesday that the company aims to build artificial intelligence (AI)-centric data centres and future-proof workplaces for enterprise customers."We want to help you (enterprises) build AI-ready data centres. We want to help you future-proof your workplace. And we want to do that with an underlying layer of digital resilience," Chuck Robbins, chairman and chief executive, Cisco Systems said.Robbins was speaking at the Cisco Live 2025 annual conference.The US multinational said that it would transform data centres to power AI workloads anywhere."We need seamless operations, observability, and security everywhere. We want to help you (enterprises) do this with technologies like Secure AI Factory that we have announced with Nvidia," Robbins said.Cisco has doubled down on partnership with Jensen Huang-headed Nvidia.The two companies enable enterprises to have access to a secure and scalable platform to fast-forward the creation and deployment of AI solutions to drive business value.Founded by Leonard Bosack and Sandy Lerner back in 1984, the company said that it could facilitate enterprise customers with "massive innovation" enabling them to modernise and reimagine data centres with solutions such as Expanded AI Pods, Unified Nexus Dashboard."So we need a huge amount of security into the underlying network in order to be able to apply network services. We believe that we have a meaningful role to play."The top executive said that Cisco offers a combination of networking and security offerings which acts as a key strength which its rivals lack.The San Jose-based multinational said that Cisco is foundational to data centre build outs worldwide, and offering "critical infrastructure" catering to the AI era.Cisco has also partnered with OpenAI, and is working on its newly-released Codex software engineering agent that allows network engineers access tools for writing, testing and building code.Robbins further said that the fusion of security with the network would be critical for agentic AI.Last month, Cisco and G42 extended their strategic partnership to drive AI innovation across the United Arab Emirates (UAE) and the United States.The company collaborated with the AI Infrastructure Partnership (AIP), led by BlackRock, Global Infrastructure Partners (GIP), MGX, Microsoft and Nvidia.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
&w=3840&q=100)
Business Standard
35 minutes ago
- Business Standard
AI experts divided over Apple's research on large reasoning model accuracy
A recent study by tech giant Apple claiming that the accuracy of frontier large reasoning models (LRMs) declines as task complexity increases, and eventually collapses altogether, has led to differing views among experts in the artificial intelligence (AI) world. The paper titled 'The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity' was published by Apple last week. Apple, in its paper, said it conducted experiments across diverse puzzles which show that such LRMs face a complete accuracy collapse beyond certain complexities. While their reasoning efforts increase with the complexity of a problem till a point, it then declines despite having an adequate token budget. A token budget for large language models (LLM) refers to the practice of setting a limit on the number of tokens an LLM can use for a specific task. The paper is co-authored by Samy Bengio, senior director, AI and ML research at Apple who is also the brother of Yoshua Bengio, often referred to as the godfather of AI. Meanwhile, AI company Anthropic, backed by Amazon, countered Apple's claims in a separate paper, saying that the 'findings primarily reflect experimental design limitations rather than fundamental reasoning failures.' 'Their central finding has significant implications for AI reasoning research. However, our analysis reveals that these apparent failures stem from experimental design choices rather than inherent model limitations,' it said. Mayank Gupta, founder of Swift Anytime, currently building an AI product on stealth, told Business Standard that both sides have equally important points. 'What this tells me is that we're still figuring out how to measure reasoning in LRMs the right way. The models are improving rapidly, but our evaluation tools haven't caught up. We need tools that separate how well an LRM reasons from how well it generates output and that's where the real breakthrough lies,' he said. Gary Marcus, a US academic, who has become a voice of caution on the capabilities of AI models, said in a best case scenario, these models can write python code, supplementing their own weaknesses with outside symbolic code, but even this is not reliable. 'What this means for business and society is that you can't simply drop o3 or Claude into some complex problem and expect it to work reliably,' he wrote in his blog, Marcus on AI. The Apple researchers conducted experiments comparing thinking and non-thinking model pairs across controlled puzzle environments. 'The most interesting regime is the third regime where problem complexity is higher and the performance of both models have collapsed to zero. Results show that while thinking models delay this collapse, they also ultimately encounter the same fundamental limitations as their non-thinking counterparts,' they wrote. Apple's observations in the paper perhaps can explain why the iPhone maker has been slow to embed AI across its products or operating systems, a point on which it was criticised at the Worldwide Developers Conference (WWDC) last week. This approach is opposite to the ones adopted by Microsoft-backed OpenAI, Meta, and Google, who are spending billions to build more sophisticated frontier models to solve more complex tasks. However, there are other voices too who believe that Apple's paper has its limitations. Ethan Mollick, associate professor at the Wharton School who studies the effects of AI on work, entrepreneurship, and education, mentioned on X that while the limits of reasoning models are useful, it is premature to say that LLMs are hitting a wall.
NDTV
2 hours ago
- NDTV
US-China Trade Talks Leave Military-Use Rare Earth Issue Unsettled: Sources
Beijing: The renewed US-China trade truce struck in London left a key area of export restrictions tied to national security untouched, an unresolved conflict that threatens a more comprehensive deal, two people briefed on detailed outcomes of the talks told Reuters. Beijing has not committed to grant export clearance for some specialized rare-earth magnets that US military suppliers need for fighter jets and missile systems, the people said. The United States maintains export curbs on China's purchases of advanced artificial intelligence chips out of concern that they also have military applications. At talks in London last week, China's negotiators appeared to link progress in lifting export controls on military-use rare earth magnets with the longstanding US curbs on exports of the most advanced AI chips to China. That marked a new twist in trade talks that began with opioid trafficking, tariff rates and China's trade surplus, but have since shifted to focus on export controls. In addition, US officials also signalled they are looking to extend existing tariffs on China for a further 90 days beyond the August 10 deadline agreed in Geneva last month, both sources said, suggesting a more permanent trade deal between the world's two largest economies is unlikely before then. The two people who spoke to Reuters about the London talks requested not to be named because both sides have tightly controlled disclosure. The White House, State Department and Department of Commerce did not immediately respond to requests for comment. China's Foreign and Commerce ministries did not respond to faxed requests for comment. President Donald Trump said on Wednesday the handshake deal reached in London between American and Chinese negotiators was a "great deal," adding, "we have everything we need, and we're going to do very well with it. And hopefully they are too." And US Treasury Secretary Scott Bessent said there would be no "quid pro quo" on easing curbs on exports of AI chips to China in exchange for access to rare earths. China Chokehold But China's chokehold on the rare earth magnets needed for weapons systems remains a potential flashpoint. China dominates global production of rare earths and holds a virtual monopoly on refining and processing. A deal reached in Geneva last month to reduce bilateral tariffs from crushing triple-digit levels had faltered over Beijing's restrictions on critical minerals exports that took shape in April. That prompted the Trump administration to respond with export controls preventing shipments of semiconductor design software, jet engines for Chinese-made planes and other goods to China. At the London talks, China promised to fast-track approval of rare-earth export applications from non-military US manufacturers out of the tens of thousands currently pending, one of the sources said. Those licenses will have a six-month term. Beijing also offered to set up a "green channel" for expediting license approvals from trusted US companies. Initial signals were positive, with Chinese rare-earths magnet producer JL MAG Rare-Earth, saying on Wednesday it had obtained export licences that included the United States, while China's Commerce Ministry confirmed it had approved some "compliant applications" for export licences. But China has not budged on specialized rare earths, including samarium, which are needed for military applications and are outside the fast-track agreed in London, the two people said. Automakers and other manufacturers largely need other rare earth magnets, including dysprosium and terbium. Big Issues Remain The rushed trade meeting in London followed a call last week between Trump and Chinese leader Xi Jinping. Trump said US tariffs would be set at 55% for China, while China had agreed to 10% from the United States. Trump initially imposed tariffs on China as punishment for its massive trade surplus to the United States and over what he says is Beijing's failure to stem the flow of the powerful opioid fentanyl into the US Chinese analysts are pessimistic about the likelihood of further breakthroughs before the August 10 deadline agreed in Geneva. "Temporary mutual accommodation of some concerns is possible but the fundamental issue of the trade imbalance cannot be resolved within this timeframe, and possibly during Trump's remaining term," said Liu Weidong, a US-China expert at the Institute of American Studies, Chinese Academy of Social Sciences. An extension of the August deadline could allow the Trump administration more time to establish an alternative legal claim for setting higher tariffs on China under the Section 301 authority of the USTR in case Trump loses the ongoing legal challenge to the tariffs in US court, one of the people with knowledge of the London talks said. The unresolved issues underscore the difficulty the Trump administration faces in pushing its trade agenda with China because of Beijing's control of rare earths and its willingness to use that as leverage with Washington, said Ryan Hass, director of the John L. Thornton China Center at the Brookings Institution. "It has taken the Trump team a few punches in the nose to recognise that they will no longer be able to secure another trade agreement with China that disproportionately addresses Trump's priorities," Hass said.
NDTV
3 hours ago
- NDTV
Nearly 7,000 UK University Students Caught Cheating Using AI: Report
Nearly 7,000 university students in the UK were caught cheating using ChatGPT and other artificial intelligence tools during the 2023-24 academic year, according to data obtained by The Guardian. As part of the investigation, the British newspaper contacted 155 universities under the Freedom of Information Act. Of those, 131 institutions responded. The latest figures show 5.1 confirmed cases of AI-related cheating for every 1,000 students, a rise from 1.6 per 1,000 the previous year. Early projections for the current academic cycle suggest the number could climb even higher to 7.5 per 1,000 students. The growing reliance on AI tools like ChatGPT is proving to be a major challenge for higher education institutions. At the same time, cases of traditional plagiarism have dropped. From 19 per 1,000 students in 2019-20 to 15.2 last year, the number has gone down and is expected to fall further to 8.5 per 1,000. Experts warn that the recorded cases may be only scratching the surface. "I would imagine those caught represent the tip of the iceberg," said Dr Peter Scarfe, associate professor of psychology at the University of Reading. "AI detection is very unlike plagiarism, where you can confirm the copied text. As a result, in a situation where you suspect the use of AI, it is near impossible to prove, regardless of the percentage AI that your AI detector says (if you use one). This is coupled with not wanting to falsely accuse students." Evidence suggests AI misuse is far more widespread than reported. A February survey by the Higher Education Policy Institute found that 88 per cent of students admitted to using AI for assessments. Researchers at the University of Reading tested their own systems last year and found AI-generated submissions went undetected 94 per cent of the time. Online platforms are making it easier. The report found dozens of videos on TikTok promoting AI paraphrasing and essay-writing tools that help students bypass standard university detectors by "humanising" ChatGPT-generated content. Dr Thomas Lancaster, an academic integrity researcher at Imperial College London, said, "When used well and by a student who knows how to edit the output, AI misuse is very hard to prove. My hope is that students are still learning through this process." Science and technology secretary Peter Kyle told The Guardian that AI should be used to "level up" opportunities for dyslexic children. Tech giants are already targeting students as key users. Google offers university students a free 15-month upgrade to its Gemini AI tool, while OpenAI provides discounted access to students in the US and Canada.
