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AMD unveils advanced chips with lighting AI training speed

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Advanced Micro Devices (AMD) has launched a series of cutting-edge chips designed to supercharge the speed of artificial intelligence (AI) training.

 

 

With an emphasis on faster processing and improved efficiency, these new chips are set to redefine the capabilities of AI-driven applications across various industries.

The latest AMD chips boast an innovative architecture that significantly enhances the performance of AI training tasks, ranging from machine learning algorithms to neural network simulations.

This development addresses a critical need in the rapidly evolving field of AI, where speed and efficiency are paramount for handling complex computations and accelerating breakthroughs in research and development.

These chips are poised to revolutionise the landscape of AI-powered technologies, offering a competitive edge to businesses and researchers alike.

The enhanced processing power enables quicker training of AI models, unlocking the potential for more sophisticated applications such as advanced image recognition, natural language processing, and autonomous systems. As industries continue to embrace AI, the release of these chips underscores AMD’s commitment to pushing the boundaries of technology.

In the race to dominate the AI hardware market, AMD’s latest release positions the company as a formidable player alongside industry giants. As demand for faster and more efficient AI solutions grows, the impact of these chips on the development and deployment of AI applications is expected to be substantial.

The unveiling of these advanced chips not only marks a significant milestone for AMD but also signals a new era in the evolution of AI technologies.

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Australia’s workforce revolution sets the stage for a four-day work week

Australia’s AI Workforce Revolution: Automation Paves the Way for a Four-Day Work Week and New Job Redesigns.

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Australia’s AI workforce revolution: automation paves the way for a four-day work week.

In Short

UiPath’s report highlights the rapid shift towards “agentic automation,” where AI makes autonomous decisions, encouraging businesses to reassess roles and harness automation for productivity. This evolution may enable a four-day work week and necessitates the retraining of staff while ensuring regulations are in place for trust and compliance with AI integration.

The trend towards work reallocation is rapidly advancing, with UiPath’s new report identifying significant shifts in AI and automation.

Key insights from the report suggest a move towards “agentic automation,” where AI begins to make autonomous decisions. Yelena GalstianHead of Solutions and Customer Advisory at UiPath shares her key insights.

Organisations are encouraged to reassess existing roles and identify areas where automation can enhance productivity.

A critical aspect will be the orchestration of collaboration between human employees, AI agents, and software robots to ensure effective teamwork.

Looking ahead, the motto for businesses is to “redesign and reassign” processes while considering how AI can handle repetitive tasks, allowing human employees to focus on more complex responsibilities.

As organisations embrace these changes, we could see a potential transition to a four-day work week, made feasible through increased efficiency and productivity from AI.

For further insights into the research and methodologies for implementing AI in business, interested parties can connect with the UiPath team through their website.

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Data centres pushed to breaking point as AI demands surge

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The hidden cost of AI’s unstoppable growth

The rise of AI is pushing data centres to their limits, with increasing demands for high-resolution telemetry and greater power capacity. As AI applications grow more complex, managing these challenges efficiently has become a critical focus for industry leaders. The quest for smarter solutions is reshaping the infrastructure landscape. Luke Dalske, COO of Radix IoT, joins the program to discuss.

 

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AI’s role in transforming supply chains: Efficiency, forecasting, optimisation

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AI is transforming supply chains: enhancing efficiency, demand forecasting, delivery optimisation through advanced technologies.

Supply chain issues continue to challenge industries worldwide.

AI is increasingly seen as a solution to enhance efficiency and resilience within this sector.

To understand its impact, Jyot Singh, CEO of RTS Labs, joined to share his insights.

By utilising historical data, algorithms can predict future demand, facilitating better inventory management.

Additionally, advances in generative AI further enhance these forecasts by incorporating sentiment analysis and other factors.

AI also optimises delivery routes by analysing real-time data on traffic and weather conditions, thus reducing costs.

Companies, such as UPS, utilise technologies to streamline last-mile delivery, which is the most expensive portion of the supply chain.

AI’s role extends to improving vendor management and procurement efficiency through smart contracts and data-driven decision-making.

This helps businesses assess vendor reliability and make informed choices about allocating resources effectively.

Moreover, the digital twin technology allows businesses to simulate their supply chains virtually, testing various scenarios to identify potential disruptions.

American technological research and consulting firm Gartner predicts that by 2026, 60% of global supply chains will adopt digital twin applications, enhancing their ability to manage complex logistics.

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