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MIT and Microsoft Introduce Murakkab to Streamline AI Workflows and Reduce Cloud Costs

MIT and Microsoft have developed Murakkab, an AI system that optimizes agentic workflows, reducing cloud computing costs, energy use and resource demands.

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Illustration of cloud computing services with interconnected cloud icons, servers, software, and computer systems displayed above a person typing on a laptop keyboard.
A conceptual illustration of cloud-based computing infrastructure, highlighting interconnected services, software and data systems used to power AI workloads and cloud applications. Image credit: Tadamichi/iStock

As AI systems increasingly rely on multiple models working together to complete complex tasks, the computing infrastructure needed to run them has become more resource-intensive. Researchers at the Massachusetts Institute of Technology (MIT) and Microsoft have introduced Murakkab AI system, an automated system designed to improve how these AI workflows are built and deployed. By selecting the most efficient combination of AI models, software tools and computing resources, the system reduces computational demand, lowers cloud operating costs and cuts energy consumption without affecting performance.

Named after the Urdu word meaning “a composition of things,” Murakkab is designed to optimize the entire lifecycle of an agentic workflow, from application design to cloud deployment.

Murakkab AI System Simplifying Complex AI Workflows

Many modern AI applications are powered by agentic workflows, multi-step systems that coordinate several AI models and external tools, such as databases and programming environments, to complete tasks ranging from video analysis to code generation. Configuring these workflows typically requires developers to manually choose models, define execution sequences and allocate computing resources, making deployment both time-consuming and resource-intensive.

Murakkab AI System
A conceptual illustration of AI-powered workflows, showing digital task management and automated resource allocation used to optimize cloud computing and agentic AI applications. Image credit: Bongkod Worakandecha/iStock

Murakkab, which will be presented at the upcoming USENIX Symposium on Operating Systems Design and Implementation, replaces much of that manual process. Developers only need to describe the application’s objective in plain language. The system then determines which AI models and tools are best suited for the task while selecting the most efficient hardware configuration and resource allocation for cloud deployment.

Optimizing Resources in Real Time

Beyond configuring workflows, Murakkab continuously adjusts computing resources during execution based on user-defined priorities, such as lowering deployment costs or improving response times.

In evaluations across multiple agentic workloads, the system required fewer computational units than conventional deployment approaches, reducing both energy consumption and infrastructure costs while maintaining comparable application performance.

Speaking during a press briefing, Gohar Chaudhry, lead author of the study, said the rapid growth of agentic AI systems has made resource optimization increasingly important.

“Agentic workflows are getting very complicated and quickly becoming the backbone of what cloud providers are doing. Energy usage is a huge concern, so we need to be very careful about how efficient these workflows are. It is very easy to over-allocate resources, wasting energy and money. Enabling a cloud provider to intelligently make these workflows more resource-optimal is a win for everyone involved,” Chaudhry said.

The research was conducted by Chaudhry along with Adam Belay, associate professor in MIT’s Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), Ricardo Bianchini, technical fellow and corporate vice president at Microsoft Azure, and other Microsoft Azure researchers.

Why Existing AI Workflows Waste Resources

Traditional agentic workflows require developers to make numerous technical decisions in advance, including selecting AI models, defining the sequence in which AI agents interact and choosing the hardware resources needed for deployment. Because these workflows often combine proprietary models and tools from multiple providers, introducing a newly released AI model or updating an existing workflow can require extensive reconfiguration.

The researchers said the enormous number of possible combinations makes manual optimization increasingly difficult.

“Even if you wanted to do all this manually, it is unlikely that you’ll be able to configure the workflow optimally because the space of possible configurations is so large,” said Chaudhry.

Murakkab also addresses a key challenge for cloud providers, which often over-allocate computing resources because they have limited visibility into how agentic workflows operate internally. The system automatically selects suitable hardware and adjusts resource allocation during execution, reducing unnecessary computation and energy use while maintaining performance.

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Apple Price Hike in India: Macs, iPads Get Costlier as AI Memory Costs Surge

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Apple logo displayed outside an Apple Store after the company announced a price hike for MacBooks and iPads in India.
Apple has increased the prices of MacBooks, iPads and other products in India amid rising AI-driven memory chip costs. (Representative image) Image credits: Laurenz Heymann/ Pexels

Apple has announced a price hike in India for several of its products, including MacBooks, iPads, Apple TV and HomePod devices, as rising global memory chip costs driven by artificial intelligence (AI) infrastructure increase manufacturing expenses. iPhone prices remain unchanged.

The revised prices are now reflected on Apple’s India online store and come amid a global surge in demand for DRAM and NAND flash memory, essential components used in laptops, tablets and other consumer electronics.

MacBook Prices See Sharp Increase

Among the biggest revisions, the 13-inch MacBook Air (M5) now starts at ₹1,49,900, up from ₹1,19,900. The 15-inch MacBook Air (M5) has increased from ₹1,44,900 to ₹1,74,900.

Meanwhile, the 14-inch MacBook Pro now starts at ₹2,39,900, compared to its earlier price of ₹1,69,900. Premium MacBook Pro models equipped with the M5 Max chip have also witnessed price increases of up to ₹1 lakh.

iPad Prices Also Revised

Apple has also increased prices across several iPad models. The entry-level 11-inch iPad now starts at ₹49,900, up from ₹34,900, while the 11-inch iPad Air has risen from ₹59,900 to ₹74,900. The 11-inch iPad Pro now starts at ₹1,19,900, compared with ₹99,900 earlier.

Apple TV and Home Pod devices have also become more expensive, although the company has not revised prices for iPhones, Apple Watches or AirPods.

Why Has Apple Increased Prices?

According to Reuters, Apple attributed the revision to rising costs of memory components such as DRAM and NAND flash storage.

The rapid expansion of AI data centres has significantly increased demand for advanced memory chips, tightening global supply and driving up component prices. Industry analysts say manufacturers across the consumer electronics sector are facing higher production costs as AI infrastructure investment continues to accelerate.

Why iPhone Prices Remain Unchanged

Despite the latest revision, Apple has kept iPhone prices in India unchanged. Analysts believe the company may be waiting until the launch of its next-generation iPhone lineup before making any pricing changes to its smartphones. However, continued increases in semiconductor costs could influence future pricing decisions.

AI Boom Reshaping Consumer Electronics

The price hike in India highlights the wider impact of the AI boom on the technology industry. As companies invest billions of dollars in AI infrastructure and data centres, demand for high-performance memory chips has surged, increasing manufacturing costs for laptops, tablets and other electronic devices.

The development reflects a broader trend where AI is beginning to influence not only software innovation but also the pricing of consumer hardware worldwide.

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As AI Transforms Work, Can India Manage the Jobless Growth?

As AI transforms workplaces, concerns over jobless growth are rising. Experts and global leaders discuss about employment through reskilling and education.

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Jobless growth
A representational image of AI competing with humans. Image credits: Pavel Danilyuk/ Pexels

“We have to upskill ourselves every six months now. Earlier, learning a new software was enough. Today, the competition is not just with other people. It is with AI.”

For Vishnu, a customer service professional at Infopark in Kochi, keeping pace with technological change has become part of the job. New AI-powered tools are increasingly handling routine customer queries, summarizing conversations and assisting with problem-solving—tasks that once relied entirely on human workers.

His experience reflects a broader shift taking place across industries. As artificial intelligence becomes more capable, workers are being pushed to continuously adapt, raising concerns about whether technological progress will create enough employment opportunities to match its economic gains.

The global economy is undergoing one of its most significant technological transformations since the internet age. Yet alongside optimism about innovation and productivity, policymakers and business leaders are grappling with a growing concern: jobless growth.

What happens in jobless growth?

The issue took centre stage this week at the World Economic Forum’s Annual Meeting of the New Champions, popularly known as “Summer Davos,” in Dalian, China. The gathering brought together more than 1,800 leaders from governments, businesses and academia from over 90 countries to discuss how emerging technologies can drive economic growth while ensuring that workers are not left behind.

A recurring theme throughout the summit was the need to prevent economic growth from becoming detached from job creation. While artificial intelligence is expected to improve productivity across sectors, leaders stressed that technology alone cannot guarantee employment opportunities. Investments in skills, education, entrepreneurship and workforce transition were repeatedly highlighted as essential to ensuring that innovation benefits a wider section of society.

The concern is not without basis.

According to the World Economic Forum’s Future of Jobs Report 2025, technological change is expected to transform 22 percent of jobs globally by 2030. The report estimates that while around 170 million new jobs could be created during this period, approximately 92 million existing jobs may be displaced, resulting in a large-scale restructuring of the labour market.

The report also found that nearly 59 percent of the global workforce will require reskilling or upskilling by 2030. Meanwhile, 41 percent of employers surveyed said they expect to reduce workforces where artificial intelligence can automate specific tasks, even as a majority indicated plans to invest in retraining employees.

Why is India significant?

Home to one of the world’s largest young populations, the country adds millions of job seekers to the workforce every year. At the same time, sectors such as information technology, customer support, finance and administrative services—areas where India has built a strong global presence—are among those experiencing rapid AI adoption.

Research by the International Labour Organization has suggested that generative AI is more likely to transform jobs than eliminate them entirely. Many occupations, particularly in clerical and support services, are expected to see specific tasks automated rather than whole roles disappearing. This means workers may increasingly find themselves collaborating with AI systems instead of competing directly against them.

That possibility has shifted attention toward preparedness rather than panic.

Rather than debating whether AI will change the nature of work, attention is increasingly shifting to how workers can be prepared for that change. Policymakers, educational institutions and employers are under growing pressure to ensure that people have access to the skills needed in an AI-driven economy. From digital literacy and vocational training to continuous learning opportunities, reskilling is emerging as a key part of the response.

The World Economic Forum echoed this sentiment in Dalian, emphasizing that the next phase of economic growth will depend not only on technological breakthroughs but also on investments in human capital.

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10 Technologies That Could Change How We Power Homes, Fight Cancer and Feed the World

The report identifies a new generation of technologies that are moving from laboratories into practical applications and could begin influencing everyday life within the next three to five years

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Image: AI-generated

The next technological revolution may not arrive through a single invention. Instead, it could emerge from a collection of breakthroughs that reshape how people access energy, healthcare, food and essential resources.

That is the picture painted by the World Economic Forum’s Top 10 Emerging Technologies Report 2026, produced in collaboration with scientific publisher Frontiers. The report identifies a new generation of technologies that are moving from laboratories into practical applications and could begin influencing everyday life within the next three to five years.

What makes this year’s list particularly striking is a common thread connecting many of the innovations. They are designed to make critical resources—whether electricity, medicines or industrial materials—more accessible, more efficient and less dependent on geography or large centralized systems.

Emerging Technologies 2026 Are Bringing Energy Closer to People

For more than a century, electricity has largely travelled in one direction—from power stations to homes and businesses. That model may soon begin to change.

One of the technologies highlighted in the report is Everything-to-Grid Energy, or X-to-Grid. The concept allows buildings, electric vehicles, factories and even data centres to send stored electricity back into the grid during periods of high demand. Instead of acting solely as consumers, these assets become active participants in energy generation and storage.

Combined with the rapid growth of renewable energy, such systems could make electricity networks more resilient and reduce waste.

Another energy-related breakthrough is Direct Lithium Extraction, which dramatically shortens the time required to recover lithium from brine sources. Lithium is a critical component of electric vehicle batteries and energy storage systems. Faster and more sustainable extraction methods could strengthen supply chains while reducing environmental impacts.

Meanwhile, Passive Radiative Cooling Materials offer a low-energy response to rising temperatures. These materials cool buildings by reflecting sunlight and releasing heat into the atmosphere, reducing the need for conventional air-conditioning systems. In a warming world, such innovations could become increasingly important.

Emerging Technologies 2026 Could Transform Healthcare

Healthcare is another field undergoing rapid transformation.

Among the technologies attracting attention are Personalized mRNA Cancer Vaccines, which are designed around the unique genetic mutations present in an individual patient’s tumour. Unlike conventional treatments, these vaccines train the immune system to recognise and attack specific cancer cells, potentially reducing the likelihood of recurrence.

Researchers are also making progress with Exosome Drug Delivery, a technique that uses naturally occurring particles produced by cells to transport medicines directly to targeted areas of the body. Scientists believe this approach could eventually help deliver treatments to difficult-to-reach locations, including parts of the brain.

The report further highlights Quantum Simulation for Drug Discovery, which uses advanced computational models to understand molecular interactions with unprecedented precision. If successful at scale, such systems could shorten drug development timelines and reduce costs, accelerating the arrival of new therapies.

Together, these technologies point towards a future in which medicine becomes increasingly personalised, predictive and precise.

Emerging Technologies 2026 Aim to Tackle Climate and Resource Challenges

Many of the technologies featured in the report are aimed at addressing environmental pressures and resource constraints.

One example is PFAS Destruction, designed to eliminate so-called “forever chemicals” that can persist in water supplies and ecosystems for decades. Traditional treatment methods often struggle to break down these substances, but emerging approaches are showing promising results.

Another notable innovation is Precision Fermentation, which uses microorganisms such as yeast and bacteria to produce ingredients, chemicals and materials more efficiently than conventional manufacturing methods. The technology has applications across food production, pharmaceuticals and industrial manufacturing while requiring fewer natural resources.

Such advances reflect a growing effort to decouple economic growth from resource-intensive production systems.

Emerging Technologies 2026 Reveal the Next Frontier of AI and Computing

Artificial intelligence continues to evolve beyond today’s machine-learning models.

The report highlights World Models, a new class of AI systems capable of building sophisticated representations of physical environments. By combining multiple forms of data, these systems may help machines better predict outcomes, plan actions and interact with the real world. Applications could range from robotics and autonomous vehicles to industrial automation.

At the same time, advances in quantum computing are forcing researchers to rethink cybersecurity.

One response is Lattice-Based Cryptography, a form of encryption designed to remain secure even against future quantum computers. As quantum machines become more powerful, such technologies may play a crucial role in protecting financial systems, government infrastructure and personal data.

A Future That Is More Local, Personal and Resilient

Viewed individually, each of these technologies addresses a specific challenge. Together, however, they reveal a broader trend.

Energy generation is becoming more distributed. Healthcare is becoming more personalised. Manufacturing is becoming more efficient. Critical resources are moving closer to the people who need them.

The World Economic Forum notes that scientific breakthroughs alone are not enough. Infrastructure, regulation, investment and public trust will ultimately determine whether these innovations achieve widespread adoption. Technologies that perform well in laboratories often face significant hurdles when scaled to real-world conditions.

Yet the report offers a glimpse of a future that looks markedly different from today’s systems—one where energy, healthcare and essential resources are more accessible, adaptable and resilient.

The coming decade may reveal whether these emerging technologies remain promising experiments or become the foundations of everyday life.

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