Rapidus Wants to Offer Fully Automated Packaging for 2nm Fab to Cut Chip Lead Times - Related to better, data, no-code,, ai,, automated

Better together: AI, no-code, and the human workforce

In 2022, the AI boom took the world by storm, sparking up conversations about its impact on society and asking the burning question: Does it have the power to take our jobs?

McKinsey conducted a study on the topic of AI and its potential consequences for the human workforce. Concluding that 15% of the global workforce may have their job replaced by AI come 2030. This justifiably raised concerns about job displacement, particularly in sectors where generative AI has shown significant potential, such as customer service, digital marketing. And data entry. Two years down the line, the initial buzz and clamor has calmed down — but the question still stands. While headlines continued to paint a grim picture of a workforce rendered obsolete, this narrative overlooks a crucial element; the potential for AI to empower humans and. Free them up to fully apply their creativity to create new opportunities.

The truth is: there’s no black-and-white answer. The reality is a more nuanced picture. To truly unlock the potential of AI in the working world, there needs to be a shift in perspective in how we think about work.

Burley Kawasaki Social Links Navigation Global VP of Product Marketing and Strategy at Creatio.

Historically. Technological advancements have led to new jobs and industries. For instance, when the internet was first formed, 500,000 jobs had been destroyed, but. Generated a net total of million new opportunities — more than doubling the number of roles lost. The same logic applies to AI.

The momentum to push AI as a tool for businesses is timely. As the dust settles on the Autumn Budget Statement which disappointed many UK tech leaders. With AI investment initiatives already pausing earlier this year, the announcement once again neglected to fulfill its promise set out in the last statement, running the risk of stalling and. Falling behind in the race to harness the power of AI. With the government slow to step up, ultimately, the buck stops with businesses — not government spending — to drive AI adoption. This means reimagining the future workforce, applying AI’s immense potential to augment human capabilities, rather than simply replacing them, as fear-mongering media narratives suggest.

AI and automation are working hand-in-hand. Transforming the workplace by significantly reducing repetitive, manual tasks. Arduous data entry processes can be automated, complex calculations can be performed in seconds, and reports can be generated. Though minimal human intervention is required, it’s key to recognize that this doesn’t take specialists out of the picture; it only works to empower them further. By allowing employees to focus on higher-level strategy, creativity, and relationship building, the impact of AI is fundamentally changing how existing jobs are performed, making them more efficient and productive, rather than bogged down in manual data analysis.

What’s more. AI is already creating new job opportunities, particularly in fields related to AI development, implementation and maintenance. We're seeing a rise in new roles like AI trainers, ethicists, and prompt engineers, jobs that didn't exist just a few years ago. This highlights how AI isn’t merely automating existing tasks but also creating entirely new avenues for employment.

The trifecta for success: AI, no-code and the human workforce.

Alongside the rise of AI, another workforce transformation is brewing: No-code technology.

AI has offered tremendous advantages for breakthroughs in innovation. But many businesses have been slowed because of the required technical experience and a shortage of AI-trained developers. No-code essentially takes a less technical approach to AI software development that democratizes technology, allowing non-IT employees to build AI-powered applications without extensive programming skills. With enhanced accessibility, businesses are empowered to take coding and development into their own hands. Individuals can build and deploy flexible AI applications that automate workflows, build custom solutions, and enhance overall efficiency, regardless of their programming background.

Automation equals time saved, freeing both developers and. Business people up for higher-value tasks and fostering a stronger culture of innovation. The combination of AI plus no-code is also tilting the balance away from shrink-wrapped, vanilla off-the-shelf software and. Increasing the trend again towards highly customized AI-infused apps. people have been trained to avoid customizing packaged software because they wanted to lower the cost and complexity they would face if they did so. However, AI + no-code represents a new alternative that offers the best of both worlds – you can tailor the process and app to your needs, but. Without the cost and risk.

John Bratincevic, Principal Analyst at Forrester Research puts it this way: “There are good reasons for this. When practical, fit-to-purpose software is best. And the lower cost, risk, and lead time of low-code development — coupled with an expanded developer pool, easier integration, management of apps on a common platform. Leveraged licensing, etc. — makes it much harder to justify off-the-shelf software licenses and vendor sprawl. AI-powered enterprises will “build” software instead of “buy” it — and many applications in enterprise portfolios will consolidate onto low-code AppGen platforms.”.

While no-code makes complex technology accessible, AI also brings new intelligent automation and. Data-driven insights to the table. By forging these two tools together, businesses can form a powerful combination that reshapes and transforms the capabilities of the human workforce. This synergy can play out in a variety of ways. One example includes data visualization dashboards, where AI analyses data and extracts valuable insights to be displayed on a no-code-built dashboard; then acts upon this by having an AI agent or AI-powered workflow automate the necessary updates to systems. Documents or taking action on the user’s behalf. While AI and no-code may accelerate developing new apps, the role of human analysts play a crucial role in interpreting those insights, identifying patterns, and making strategic decisions and actions (supported by AI) that strengthen the organization's bottom line.

By embracing technologies like AI and no-code, organizations can unlock greater potential from the workforce and. Work toward a future where technology and people thrive together — not compete for the flag at the top of the mountain.

While the uncertainty surrounding AI’s role in replacing jobs remains strong, the future of work is not pre-determined. This is just the beginning of a long journey ahead. The onus is on businesses to lead the way in ethical and strategic AI development, while embracing new technologies such as no-code to unleash an unprecedented level of efficiency and enable the workforce to flourish.

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Mastering data overload by implementing AIOps

Today’s businesses are drowning in data from IT systems, applications and digital platforms. It’s a situation that’s been accelerated by the post-pandemic pivot towards home working and the popularity of AI, which has seen the volume of global data rise from 2 zettabytes in 2010 to a forecasted 394 zettabytes by 2028.

Managing this flood is overwhelming for IT teams, whose current approaches to data management simply can’t keep up with the exponential growth in scale and. Complexity. Without a digital life raft, they’re at risk of an information overload that could obscure data analysis, delay decision-making and impede commercial growth.

Enter AIOps, which can help businesses manage vast amounts of data by surfacing the most critical issues in real-time – allowing IT teams to address problems faster and. Allocate resources where they’re needed most. Ultimately, this technology converts having an excess of data into a significant competitive edge.

John Atkinson Social Links Navigation Director of Solutions Engineering, UK & Ireland, at Riverbed Technology.

It’s likely that the businesses struggling to cope with the complex demands of modern IT environments are those still relying on legacy software. Siloed data findings and rigid monitoring tools. The problem is, these traditional approaches typically require manual input, which is time-consuming and prone to error.

By design, they also fail to provide a holistic view of the IT ecosystem – a lack of transparency that makes it difficult to identify patterns or predict potential issues in a world where data is everywhere. What’s left is an overreliance on under-resourced IT teams that are tasked with locating, protecting and. Utilizing a completely unmanageable amount of information.

Updating or replacing these existing solutions involves considerable time and money. However, persisting with inefficient and outdated systems will likely incur ‘tech debt’ – the financial burden of constantly needing to modification aspects of a digital estate to meet the demands of new projects. Essentially, neglecting digital transformation will result in repetitive and costly business expenses moving forward. Therefore, businesses need a more proactive solution.

AIOps has the power to transform organizational IT management thanks to the way it harnesses machine learning and advanced analytics.

By allowing these platforms to oversee their data. Organizations can effortlessly deal with the technical disruptions that would otherwise be buried within increasingly complex digital estates.

AIOps doesn’t just react to issues; it predicts them too. By analyzing real-time and historical data, it detects patterns that signal future interruptions, allowing teams to act before problems impact consumers. Automating repetitive tasks frees IT professionals for strategic initiatives while streamlining processes and optimizing budgets, and platforms offering AIOps for observability provide a single window into IT ecosystems – reducing blind spots and generating insights that protect performance across applications.

AIOps enables organizations to cut through the chaos, offering a comprehensive view of digital operations and. Helping them focus on the information that truly matters to them.

The increasingly vital role of data stores.

For businesses to integrate technology that helps them comprehensively monitor the behavior of IT systems, their information needs to be easily accessible – which is exactly why data stores are another key part of the AIOps equation.

Imagine that an organization's IT infrastructure is like an office block. Just like every office space would store its own paperwork, each department in this virtual building contains different stacks of unique data. If an IT team was told to examine every bit of this information, they’d have to carefully search every siloed location to find it.

Having a data store is like putting all those siloed datasets into a ​​virtual warehouse, within which an organization's information is immediately more accessible. Analyzable and trackable. A digital asset of this nature can be the difference between a failed and a successful AI strategy.

However, an inability to build a repository large enough is often a major stumbling block for many businesses. Particularly as datasets become more immense than ever before. ​​With the help of pre-built infrastructures, IT teams needn’t worry about finding more capacity. Instead, they can reap the scalable, secure and accessible rewards of having a unified data ecosystem.

In today’s digital economy. Data isn’t just an operational byproduct. Rather, it’s a strategic asset that can support businesses to outpace their competitors by identifying trends faster, providing superior customer experiences and innovating at a higher level than the rest.

By automating the handling of data streams and consolidating disparate systems. AIOps can turn organizations into agile, data-driven enterprises. Indeed, decision-makers across all industries believe in its potential, with a recent survey revealing that 91% of businesses agree that AI provides a competitive advantage.

Take customer service as an example. A public-facing business that integrates AIOps – like a retailer, bank or airline – can swiftly resolve any data bottlenecks that would usually cause website downtime or slower transactions. Customer retention levels rise as the brand establishes itself as a reliable digital presence in the industry – as does the financial bottom line.

Surviving and thriving in the age of information.

As data continues to flood the IT landscape at an overwhelming rate. It’s a challenge for businesses still deciding what action to take. AIOps can be a life saver, by prioritizing proactive problem-solving, optimizing resources and adopting solutions like unified observability and data stores.

In fact, in an era where information is power. Organizations that embrace the transformative power of AIOps can not only survive but thrive. These digital platforms unlock heightened levels of security, efficiency and innovation, shifting the strategic focus from merely coping to growing; turning the stress of being inundated by data into a competitive advantage.

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Rapidus Wants to Offer Fully Automated Packaging for 2nm Fab to Cut Chip Lead Times

One of the core challenges that Rapidus will face when it kicks off volume production of chips on its 2nm-class process technology in 2027 is lining up clients. With Intel, Samsung, and TSMC all slated to offer their own 2nm-class nodes by that time. Rapidus will need some kind of advantage to attract clients away from its more established rivals. To that end, the business thinks they've found their edge: fully automated packaging that will allow for shorter chip lead times than manned packaging operations.

In an interview with Nikkei, Rapidus' president. Atsuyoshi Koike, outlined the enterprise's vision to use advanced packaging as a competitive edge for the new fab. The Hokkaido facility, which is currently under construction and is expecting to begin equipment installation this December, is already slated to both produce chips and. Offer advanced packaging services within the same facility, an industry first. But ultimately, Rapidus biggest plan to differentiate itself is by automating the back-end fab processes (chip packaging) to provide significantly faster turnaround times.

Rapidus is targetting back-end production in particular as, compared to front-end (lithography) production. Back-end production still heavily relies on human labor. No other advanced packaging fab has fully automated the process thus far, which provides for a degree of flexibility, but slows throughput. But with automation in place to handle this aspect of chip production, Rapidus would be able to increase chip packaging efficiency and speed. Which is crucial as chip assembly tasks become more complex. Rapidus is also collaborating with multiple Japanese suppliers to source materials for back-end production.

"In the past, Japanese chipmakers tried to keep their technology development exclusively in-house. Which pushed up development costs and made them less competitive," Koike told Nikkei. "[Rapidus plans to] open up technology that should be standardized, bringing down costs, while handling critical technology in-house."

Financially, Rapidus faces a significant challenge. Needing a total of ¥5 trillion ($35 billion) by the time mass production starts in 2027. The corporation estimates that ¥2 trillion will be required by 2025 for prototype production. While the Japanese government has provided ¥920 billion in aid, Rapidus still needs to secure substantial funding from private investors.

Due to its lack of track record and. Experience of chip production as. well as limited visibility for success, Rapidus is finding it difficult to attract private financing. The enterprise is in discussions with the government to make it easier to raise capital, including potential loan guarantees, and is hopeful that new legislation will assist in this effort.

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