#Global Process Automation Market

[anushapranu]

Global Process Automation Market is projected to reach the value of USD 142.98 billion by 2030.

Market Description: 

The Global Process Automation Market was valued at USD 109.40 billion and is projected to reach a market size of USD 142.98 billion by the end of 2030. Over the forecast period of 2025-2030, the market is projected to grow at a CAGR of 5.50%. 

➡️ 𝐃𝐨𝐰𝐧𝐥𝐨𝐚𝐝 𝐒𝐚𝐦𝐩𝐥𝐞 :@ https://tinyurl.com/yc7j6zdj

One of the long-term market drivers for process automation is the continuous advancement in digital technologies. Over the last decade, technology has evolved significantly, and businesses are increasingly adopting automation tools to streamline their processes. Automation systems are powered by technologies such as artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), and the Internet of Things (IoT), which enable businesses to perform tasks faster and with greater accuracy. 

Digital transformation has become essential for companies that want to remain competitive in a rapidly changing marketplace. Automation allows businesses to reduce human error, optimize resource allocation, and improve decision-making. For example, AI-powered process automation tools can predict system failures and schedule maintenance, reducing downtime and increasing productivity. In the long run, companies that invest in automation will experience better operational efficiency, which is why this technological advancement will continue to drive the process automation market for years to come. 

The COVID-19 pandemic had a significant impact on the process automation market. The global health crisis disrupted supply chains, caused labor shortages, and forced companies to adapt to new ways of working. The pandemic highlighted the vulnerabilities of manual, human-dependent processes and the need for more efficient, automated systems. 

During the pandemic, businesses realized the benefits of automation in ensuring business continuity while maintaining health and safety standards. Automation helped companies continue operations remotely, allowing workers to oversee processes from a distance. Industries such as manufacturing, healthcare, and logistics, which faced disruptions during the pandemic, turned to automation to minimize human contact and improve the resilience of their operations. As businesses recover from the pandemic, automation will remain a key focus to increase efficiency, mitigate risk, and ensure sustainability in a post-COVID world. 

In the short term, one of the primary drivers of the process automation market is the increased demand for operational efficiency. Companies are under pressure to streamline operations, reduce costs, and boost productivity, especially as businesses navigate the challenges of economic uncertainty and supply chain disruptions. Automation offers companies the ability to automate routine tasks, such as data entry, order processing, and inventory management, which allows employees to focus on more value-added activities. 

➡️ 𝐁𝐮𝐲 𝐍𝐨𝐰 :@ https://tinyurl.com/bdzmn5fk

The need for agility and faster response times has grown significantly, especially with the rise of e-commerce and customer expectations for quick delivery times. Process automation enables businesses to optimize workflows and reduce delays, which is critical in meeting customer demands. Companies that embrace automation to improve their operations will gain a competitive advantage by being able to offer better service while lowering operational costs. 

An exciting opportunity in the process automation market is the expansion of cloud-based automation solutions. Cloud computing allows businesses to access automation tools and platforms remotely, reducing the need for expensive on-premise infrastructure. This is particularly beneficial for small and medium-sized enterprises (SMEs) that may not have the resources to invest in large-scale automation systems. 

Cloud-based solutions also offer scalability, meaning businesses can easily increase or decrease their automation capabilities based on demand. The flexibility of cloud-based platforms allows companies to innovate and adopt new technologies without significant upfront costs. As cloud adoption continues to grow, it presents an excellent opportunity for vendors to introduce affordable and accessible automation solutions to a broader range of businesses, further driving market growth. 

A prominent trend in the process automation market is the increasing adoption of artificial intelligence (AI) and machine learning (ML) technologies. These advanced technologies are being integrated into automation systems to improve decision-making, enhance predictive capabilities, and enable more complex automation processes. 

AI and ML help businesses analyze vast amounts of data in real time, which allows for smarter decision-making and optimized processes. For example, in manufacturing, AI-powered automation systems can predict when a machine is likely to fail, allowing for proactive maintenance before a breakdown occurs. In logistics, AI can optimize delivery routes and inventory management, ensuring faster deliveries and reducing operational costs. 

As AI and ML continue to advance, they will play a key role in the evolution of process automation, enabling companies to automate even more complex tasks. This trend will continue to gain momentum, as businesses realize the power of combining AI with automation to drive better outcomes. 

[datastring]

Batch Fluid Bed Dryers Market Set to Hit $1,593.7 Million by 2035

The global Batch Fluid Bed Dryers market is projected to experience significant growth, rising from $697.6 million in 2024 to $1,593.7 million by 2035. The market is expected to grow at an average annual rate of 10.3% from 2024 to 2035, driven by strong demand across pharmaceutical manufacturing, food processing, chemical processing, and plastics manufacturing industries.

Access detailed report insights here - https://datastringconsulting.com/industry-analysis/batch-fluid-bed-dryers-market-research-report

Key Applications Driving Market Growth

Batch Fluid Bed Dryers play a critical role in several industries due to their ability to provide consistent, efficient, and rapid drying. In the pharmaceutical industry, these dryers are essential for preserving the integrity of sensitive ingredients during the drying process, ensuring higher quality end products. Leading pharmaceutical companies such as Novartis and Pfizer rely on these dryers for their accuracy and reliability, securing a competitive edge in the market.

In the food processing sector, Batch Fluid Bed Dryers are used for their uniform drying capabilities. These dryers help preserve the nutritional value and extend the shelf life of food products. Companies like Nestlé and Kraft Heinz utilize these systems for drying fruits, vegetables, herbs, spices, and coffee beans, benefiting from superior heat transfer and moisture removal.

Technological Advancements and Market Innovation

Technological advancements have significantly impacted the Batch Fluid Bed Dryers market, particularly in pharmaceutical and food processing sectors. Modern fluid bed dryers now offer enhanced efficiency, reduced energy consumption, and improved output quality. These innovations enable superior drying uniformity, moisture removal, and particle size reduction, making them ideal for drying powders and granules.

The integration of automation into these systems has optimized the drying process, ensuring consistent quality output while reducing human error. As a result, the Batch Fluid Bed Dryers market has seen substantial growth, driving productivity improvements, reducing resource wastage, and lowering production costs, which in turn boosts profitability and sustainability.

Industry Leadership and Competitive Landscape

The Batch Fluid Bed Dryers market is highly competitive, with key players such as GEA Group AG, Andritz AG, Bühler Holding AG, Glatt GmbH, FLSmidth & Co. A/S, ThyssenKrupp AG, and SPX Flow Technology Danmark A/S leading the market. These companies are driving innovation by focusing on developing advanced solutions for fluid bed drying technology, customizable dryers, energy-efficient designs, and automation to improve performance and reduce operational costs.

The market’s growth is supported by shifting trends in pharmaceutical manufacturing, the expansion of chemical industries, and continuous technological advancements in fluid bed drying systems. As demand for efficient and precise drying solutions continues to rise, industry players are positioned to capitalize on significant growth opportunities.

Regional Analysis and Market Dynamics

North America remains a dominant player in the Batch Fluid Bed Dryers market, driven by robust industrial growth and technological advancements in drying systems. The pharmaceutical and food processing sectors, in particular, offer substantial opportunities due to their ongoing demand for high-efficiency drying solutions.

Key drivers in the region include stringent regulatory standards focused on quality and safety in production, along with a growing preference for sustainable and energy-efficient equipment. Europe and China are also strong contributors to market growth, with significant demand from local industries and manufacturers focusing on improving productivity and sustainability.

As these regions continue to expand, emerging markets in India, Brazil, and South Africa are expected to become increasingly important, offering new revenue opportunities for manufacturers seeking to diversify their portfolios and expand their total addressable market (TAM).

About DataString Consulting

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With over 30 years of combined experience, DataString’s leadership team is well-versed in market & business research and strategy advisory across diverse sectors globally. Their expert consultants track high-growth segments within more than 15 industries and 60 sub-industries, providing actionable insights and data-driven strategies to help businesses thrive in competitive markets.

[sudiptaam]

Bakery Processing Equipment Market Global Market Size 2025–2035

Market Overview

The Bakery Processing Equipment Market was valued at USD 14.75 Billion in 2024 and is projected to reach USD 29.8 Billion by 2035, growing at a CAGR of 6.6% between 2025 and 2035. This market includes equipment like mixers, ovens, proofers, slicers, depositors, and packaging machines essential for producing baked goods such as bread, cakes, cookies, and pastries. Request Sample- https://www.metatechinsights.com/request-sample/1795

Market Drivers

Urbanization & Consumer Preferences: Increased demand for baked items driven by urban lifestyles and changing food habits.

Health-Conscious Trends: Rising demand for gluten-free, organic, and healthy baked goods pushes innovation in baking technology.

Automation & Innovation: Advanced, automated equipment ensures efficiency, consistent quality, and reduced operational costs.

Emerging Markets: Rapid expansion of bakery chains in regions like Asia-Pacific creates demand for high-capacity, automated machinery.

Full Report- https://www.metatechinsights.com/industry-insights/bakery-processing-equipment-market-1795

Market Restraint

High Initial Investment: Cost barriers for small-scale or start-up bakeries limit their ability to invest in modern, automated equipment.

Market Opportunity

Specialized Equipment: Rising interest in health-conscious baked items boosts demand for gluten-free and organic-friendly machinery.

Cold Chain Solutions: Increased demand for frozen bakery products fuels the need for cold-chain-compatible baking systems.

Segmental Analysis

By Equipment Type

Mixers – Crucial for uniform ingredient blending.

Ovens & Proofers – Aid in baking and fermentation, ideal for artisanal breads.

Dividers & Sheeters – Enhance dough shaping efficiency.

Molders – Essential for standardizing shapes.

Slicers & Packaging – Meet consumer demand for ready-to-eat and pre-packaged options.

By Application

Bread Processing – Dominates due to high global consumption.

Cakes & Pastries – Gaining traction with growing demand for premium, indulgent bakery items.

Cookies & Biscuits – Growing demand for portable, snackable baked goods.

Pizza Crust Processing – One of the fastest-expanding segments worldwide.

Regional Overview

North America

Dominant due to a mature bakery industry and constant demand for frozen and healthy baked goods.

Innovations include AI-integrated mixers and energy-efficient ovens.

Asia-Pacific

Rapidly expanding due to urbanization, rising disposable incomes, and shifting dietary habits.

Countries like India and China lead the frozen bakery sector.

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Competitive Landscape

Top players include: GEA Group, Ali Group, Heat and Control, John Bean Technologies (JBT), Baker Perkins, among others.

GEA innovates in mixing/baking systems.

Ali Group develops energy-efficient baking systems.

JBT launches holistic bakery lines.

Heat and Control emphasizes automation in mass production.

Recent Developments

Dec 2024: UN WFP donated $870,000 worth of equipment to Ukrainian bakeries near the frontlines.

Nov 2024: Monomoy Capital Partners acquired Oliver Packaging and Equipment, enhancing its portfolio in the food processing sector.

[chandupalle]

The global process automation and instrumentation market size is projected to reach USD 86.6 billion by 2027, at a CAGR of 5.5% during the forecast period.

[sophie-frm-mars]

My wife was asking me about this this morning. This is pure political fanfic, but if I were Trump and I were going to try and make America a re-industrialised nation centred around the tech industry that keeps its supply lines as entirely in-house as possible, what I would do is start (obviously) with enormous central planning. You can't "free market incentives" your way back out of the export of industrial labour overseas.

You'd copy China and make enormous State-Owned Enterprises (assuming we care about the market and want to keep playing this stupid game instead of just becoming fully communist) that would process refined minerals into components, components into parts and parts into electronics. I'd recognise the scale of this as a multi-generational project and immediately start subsidising training for more engineers, especially for people who can set up automated factory lines but also engineers in new emerging tech fields like autonomous driving, software programmers, designers, even artists since the content economy is such a huge part of what people use tech for through social media and so much art is produced digitally now anyway.

From there you want to look at the markets globally that fucking, EaglePhone or whatever these overpriced Made In Murica devices can be sold into, and at this point, given that they will be crazy expensive compared to Chinese electronics literally no matter what you do, here would be a worthwhile place to try and flex America's muscles and threaten the UK, the EU, South America, Canada and so on with tariffs or other penalties if they don't adopt a hostile policy toward Chinese electronics.

Massive central planning would be essential for the kind of societal transformation that Trump is explicitly describing, in order to have a product to sell to the rest of the world before using imperialist bullying to make other countries buy things from America instead, but here we have to return yet again to the reality of Trump's plan. There is no end goal where America is in a stronger position. If he had implemented sweeping public programs reinvesting taxes into the health of the nation (never mind the health of its citizens) in his first term, he might have been in a powerful enough position to strongarm other countries into changing the flows of global trade, but America's world influence simply is declining, and more and more rapidly, so he's just trying to make moves that make him and his friends as much money as possible while they lock the doors, pack the country up into the box it came in and set the whole thing on fire. He describes these moves using the MAGA fantasy because it gives all his supporters in the media and the general population enough to talk about to buy him time, but I don't think anyone outside his base ever thought making America great was ever his plan, so why has everyone been critiquing the tariffs as if his sincere belief was that he would achieve his stated goals with them?

We all let our enemies set the topic of the conversation all day every day and it's shocking to me

[elwenyere]

I saw a post the other day calling criticism of generative AI a moral panic, and while I do think many proprietary AI technologies are being used in deeply unethical ways, I think there is a substantial body of reporting and research on the real-world impacts of the AI boom that would trouble the comparison to a moral panic: while there *are* older cultural fears tied to negative reactions to the perceived newness of AI, many of those warnings are Luddite with a capital L - that is, they're part of a tradition of materialist critique focused on the way the technology is being deployed in the political economy. So (1) starting with the acknowledgement that a variety of machine-learning technologies were being used by researchers before the current "AI" hype cycle, and that there's evidence for the benefit of targeted use of AI techs in settings where they can be used by trained readers - say, spotting patterns in radiology scans - and (2) setting aside the fact that current proprietary LLMs in particular are largely bullshit machines, in that they confidently generate errors, incorrect citations, and falsehoods in ways humans may be less likely to detect than conventional disinformation, and (3) setting aside as well the potential impact of frequent offloading on human cognition and of widespread AI slop on our understanding of human creativity...

What are some of the material effects of the "AI" boom?

Guzzling water and electricity

The data centers needed to support AI technologies require large quantities of water to cool the processors. A to-be-released paper from the University of California Riverside and the University of Texas Arlington finds, for example, that "ChatGPT needs to 'drink' [the equivalent of] a 500 ml bottle of water for a simple conversation of roughly 20-50 questions and answers." Many of these data centers pull water from already water-stressed areas, and the processing needs of big tech companies are expanding rapidly. Microsoft alone increased its water consumption from 4,196,461 cubic meters in 2020 to 7,843,744 cubic meters in 2023. AI applications are also 100 to 1,000 times more computationally intensive than regular search functions, and as a result the electricity needs of data centers are overwhelming local power grids, and many tech giants are abandoning or delaying their plans to become carbon neutral. Google’s greenhouse gas emissions alone have increased at least 48% since 2019. And a recent analysis from The Guardian suggests the actual AI-related increase in resource use by big tech companies may be up to 662%, or 7.62 times, higher than they've officially reported.

Exploiting labor to create its datasets

Like so many other forms of "automation," generative AI technologies actually require loads of human labor to do things like tag millions of images to train computer vision for ImageNet and to filter the texts used to train LLMs to make them less racist, sexist, and homophobic. This work is deeply casualized, underpaid, and often psychologically harmful. It profits from and re-entrenches a stratified global labor market: many of the data workers used to maintain training sets are from the Global South, and one of the platforms used to buy their work is literally called the Mechanical Turk, owned by Amazon.

From an open letter written by content moderators and AI workers in Kenya to Biden: "US Big Tech companies are systemically abusing and exploiting African workers. In Kenya, these US companies are undermining the local labor laws, the country’s justice system and violating international labor standards. Our working conditions amount to modern day slavery."

Deskilling labor and demoralizing workers

The companies, hospitals, production studios, and academic institutions that have signed contracts with providers of proprietary AI have used those technologies to erode labor protections and worsen working conditions for their employees. Even when AI is not used directly to replace human workers, it is deployed as a tool for disciplining labor by deskilling the work humans perform: in other words, employers use AI tech to reduce the value of human labor (labor like grading student papers, providing customer service, consulting with patients, etc.) in order to enable the automation of previously skilled tasks. Deskilling makes it easier for companies and institutions to casualize and gigify what were previously more secure positions. It reduces pay and bargaining power for workers, forcing them into new gigs as adjuncts for its own technologies.

I can't say anything better than Tressie McMillan Cottom, so let me quote her recent piece at length: "A.I. may be a mid technology with limited use cases to justify its financial and environmental costs. But it is a stellar tool for demoralizing workers who can, in the blink of a digital eye, be categorized as waste. Whatever A.I. has the potential to become, in this political environment it is most powerful when it is aimed at demoralizing workers. This sort of mid tech would, in a perfect world, go the way of classroom TVs and MOOCs. It would find its niche, mildly reshape the way white-collar workers work and Americans would mostly forget about its promise to transform our lives. But we now live in a world where political might makes right. DOGE’s monthslong infomercial for A.I. reveals the difference that power can make to a mid technology. It does not have to be transformative to change how we live and work. In the wrong hands, mid tech is an antilabor hammer."

Enclosing knowledge production and destroying open access

OpenAI started as a non-profit, but it has now become one of the most aggressive for-profit companies in Silicon Valley. Alongside the new proprietary AIs developed by Google, Microsoft, Amazon, Meta, X, etc., OpenAI is extracting personal data and scraping copyrighted works to amass the data it needs to train their bots - even offering one-time payouts to authors to buy the rights to frack their work for AI grist - and then (or so they tell investors) they plan to sell the products back at a profit. As many critics have pointed out, proprietary AI thus works on a model of political economy similar to the 15th-19th-century capitalist project of enclosing what was formerly "the commons," or public land, to turn it into private property for the bourgeois class, who then owned the means of agricultural and industrial production. "Open"AI is built on and requires access to collective knowledge and public archives to run, but its promise to investors (the one they use to attract capital) is that it will enclose the profits generated from that knowledge for private gain.

AI companies hungry for good data to train their Large Language Models (LLMs) have also unleashed a new wave of bots that are stretching the digital infrastructure of open-access sites like Wikipedia, Project Gutenberg, and Internet Archive past capacity. As Eric Hellman writes in a recent blog post, these bots "use as many connections as you have room for. If you add capacity, they just ramp up their requests." In the process of scraping the intellectual commons, they're also trampling and trashing its benefits for truly public use.

Enriching tech oligarchs and fueling military imperialism

The names of many of the people and groups who get richer by generating speculative buzz for generative AI - Elon Musk, Mark Zuckerberg, Sam Altman, Larry Ellison - are familiar to the public because those people are currently using their wealth to purchase political influence and to win access to public resources. And it's looking increasingly likely that this political interference is motivated by the probability that the AI hype is a bubble - that the tech can never be made profitable or useful - and that tech oligarchs are hoping to keep it afloat as a speculation scheme through an infusion of public money - a.k.a. an AIG-style bailout.

In the meantime, these companies have found a growing interest from military buyers for their tech, as AI becomes a new front for "national security" imperialist growth wars. From an email written by Microsoft employee Ibtihal Aboussad, who interrupted Microsoft AI CEO Mustafa Suleyman at a live event to call him a war profiteer: "When I moved to AI Platform, I was excited to contribute to cutting-edge AI technology and its applications for the good of humanity: accessibility products, translation services, and tools to 'empower every human and organization to achieve more.' I was not informed that Microsoft would sell my work to the Israeli military and government, with the purpose of spying on and murdering journalists, doctors, aid workers, and entire civilian families. If I knew my work on transcription scenarios would help spy on and transcribe phone calls to better target Palestinians, I would not have joined this organization and contributed to genocide. I did not sign up to write code that violates human rights."

So there's a brief, non-exhaustive digest of some vectors for a critique of proprietary AI's role in the political economy. tl;dr: the first questions of material analysis are "who labors?" and "who profits/to whom does the value of that labor accrue?"

For further (and longer) reading, check out Justin Joque's Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism and Karen Hao's forthcoming Empire of AI.

[crazy-pages]

The more I read economics literature about automation trends and globalization trends (the actual economics term, not the rabid racist term) and their economic impacts on developed economies, the more I realize that the fundamental picture we have been sold these things is a lie.

The general picture of automation revolutions is that they present some way of doing work more efficiently and/or to create a better product, and so market forces simply demand it. And we have to figure out how to deal with all of the lost jobs which are resulting from this. Because even in a socialist utopia, surely it would be absurd to continue forcing people to use old and outdated technology to do work less efficiently just so they could have work to do, right? Maybe the socialist utopia will take care of people displaced by this work better, but the displacement will still happen.

Except then I start reading about the actual history in the actual economics of automation revolutions (I recommend Blood In The Machine for a history of the Luddites and the automated textile revolution in Britain). And that's not what happens even a single time. These automated revolutions increase the cost per unit to create a good! They make the quality worse! And the existing workers get displaced, and replaced with oppressed or even outright enslaved labors who make nothing in worse conditions! They didn't even actually reduce the amount of labor involved significantly, they just started working orphan slaves 80-90 hours a week rather than artisan workers doing 30-35, to "reduce" the labor involved by reducing the number of laborers. It seems like no one benefits from this. So why is it happening!?

Well the answer is simple. The machine looms were less efficient, created lower quality products, and were worse for every single person in every sector of the economy ... except insofar as that they enabled a more unequal economy. The textile industry itself made less profit. The world itself had worse and less textiles. But the machine loom owners specifically made more money, because machine rooms enabled more control over workers in ways which could be used to relegate them to an even smaller share of the smaller profits. And they didn't outcompete others by being better, they did it through regulatory capture, illegal business practices, outright fraud, and by having a pre-existing place of power in their society.

The same applies to the classic story of Ford and his great automobile factory model. Sure it produced a lot of cars at low prices, but what the history doesn't tell you is that a bunch of other automobile companies which weren't using the factory model were putting out their own cars similar cost. Sure they weren't scaling up as fast, but everyone involved was making good money and the market kept on producing more companies to fill the gap. Ford made the decision to sell to a new lower cost car market sure, but he did not make a better profit margin per dollar of car purchases than his competitors did. He made significantly worse actually because he had such hideous turnover at his factories, and his cars were of lower quality than non-factory line cars aimed at the same market could be.

So why the hell did the entire automobile industry follow in his wake? Well, because he personally was making an insane amount of money. The factory line model let him simplify the production chain in a way which cut out a lot of people who previously been making good salaries, and it let him replace well paid laborers with dirt cheap labor. (Despite the hubbub about how good Ford's factory jobs paid, they only paid well relative to other no skill no training work available. They paid much worse than the skilled laborers he fired had made.)

And the people who controlled how the car manufacturing process worked were the people who would stand to make money by switching over.

The same is true for globalization. When a berry monopoly which controls 60% of all berry sales in the US does so by importing berries from South America, from varieties optimized for durability rather than flavor, that isn't cheaper than growing them at home. Not even with the higher cost of labor in the US. Not even if you actually paid farm hands a good wage rather than by abusing undocumented workers who can't fight back as effectively. The transport costs are too high.

All across the US food sector we have examples of food monopolies exporting produce production overseas in ways that make the final product more expensive for the customer, and lower quality at the same time. Why!?

Well because it allows them to access even more vulnerable labor markets. So even though the whole pie shrinks, the company owners get a bigger enough cut of the pie to make up for it.

The lie of automation and globalization of work and the damage it does to developed economies is just that, a lie. It is not economically predestined for this stuff to happen. Alternatives are not predestined to be competed out of the market. Unless, of course, ownership of profits is concentrated in only a few hands. Unless what's being competed for isn't net profit or net service provided or net quality of goods, but how much profit you can localize in capital owners.

If that's the actual competition, and of course it is because the people making decisions for companies also own those companies, only then does job automation and the presence of exploitable overseas labor devastate economies.

If laborers actually owned their places of business piecemeal, the motivation for these kinds of economic shocks would largely dry up. Like, sure, labor saving devices get invented sometimes and you need less people to do the same work. And sure, sometimes work can be done overseas for cheaper because standards of living at lower or because there's some comparative economic advantage. But that is not actually what is happening most of the time this stuff occurs.

If there's one thing I've learned studying this stuff, it's that genuine examples of net gain automation are less common than we think, and tend to be implemented on fairly slower timelines. Same for globalization of work. What is very common is ways in which already unequal systems of ownership and decision making and profit can be made more unequal. And the only fix I can imagine is fundamentally changing and democratizing how businesses operate, and how we handle concepts of ownership.

[thoughtportal]

The etymology of the word translation—“to carry across”—conjures an image of physical labor. It is deeply relational, requiring at least two bodies, those of an author and of the person who carries the author’s words to a previously unvisited place. Let’s say we removed the laborer and replaced that person with a car. Or a train. Suddenly there is a feeling of weight lifted, certainly ease, and perhaps a little relief. But the intimacy of the earlier image no longer holds. Whether this matters has been the subject of recent debate as some publishers consider using machines to replace human translators and what that decision might mean for an ancient art.

In November, Dutch publisher Veen Bosch & Keuning (VBK), a subsidiary of Simon & Schuster, announced that it would trial the use of artificial intelligence (AI) “to assist the translation of a limited number of books.” Reactions rose in a flurry: Writers, publishers, and translators contended that AI would produce “bland” work. They lamented the possibility of lost jobs. The European Council of Literary Translators’ Associations resisted the standardization of an idiosyncratic process, stating that the imagination, understanding, and creativity that translation demands are “intrinsically human.”

VBK’s decision to incorporate AI into the editorial process may shock some but is not unprecedented. With a broad range of AI tools now available on the market, an increasing number of writers and publishers have turned to large language models (LLMs) to assist in, or contribute to, the production of creative work. As of February 2023, there were more than two hundred e-books in Amazon’s Kindle store that listed ChatGPT as an author or coauthor, according to Reuters. Maverick publishers like Spines, although small players in the global book market, plan to publish thousands of AI-generated books next year.

AI isn’t new to translation either. Literary translators sometimes input segments of their source text into AI-based technologies like Google Translate and DeepL to generate ideas for particularly thorny passages. But these tools have to be used “very carefully,” warns Seattle-based Finnish-to-English translator Lola Rogers, “because the translations it produces are error-ridden and devoid of flow or beauty.” Edward Tian, a cofounder of AI-detecting start-up GPTZero, adds that current LLMs not only do “a mediocre job at translations,” but also reflect the “majority white, English-dominated” nature of their source texts. Reiterating such worldviews and their biases runs contrary to the aim of much literary translation: to expose audiences to new perspectives. And Rogers, who was recently commissioned to use a translation tool to expedite a months-long translation process to five or six weeks, says that from her brief experiments, the time saved with machine assistance was “minimal.” French-to-English translator Louise Rogers Lalaurie shared a similarly underwhelmed account of editing poor machine-led translations.

So what’s the threat?

One area where translators are feeling the pinch is in creating samples, book excerpts translated to give general impressions of a text to potential publishers. Some publishers have been considering using AI to do this work instead. Though she is unsure whether this is because samples are being automated, Rogers says, “The number of samples I’m asked to translate has fallen precipitously in the past couple of years, making it much harder to earn a living.” A 2024 survey of Society of Authors members found that over a third of translators have lost work due to generative AI. Close to half of translators surveyed said that income from their work has decreased.

To illustrate how AI might ease the time and cost pressures inherent to translation from a publisher’s perspective, Ilan Stavans, the publisher and cofounder of Restless Books, an independent press in Amherst, Massachusetts, gives the example of a recently acquired eight-hundred-page book. To translate it, “substantial investment” would be necessary: Not only are “first-rate translators” for the source language scarce, he says, but the project would also require at least two years of dedicated work. By the time the book is translated and published, the demand the publisher once saw for the title might easily have changed. Meanwhile, the publisher would have incurred a cost much greater than if it had used LLMs, the most expensive of which—such as the premium version of ChatGPT, which costs $200 a month—is a tenth of the average cost of publishing a translation.

“It would be fast and easy,” Stavans admits, “but it would not be the right move.” Though Stavans is enthusiastic about AI’s potential and sees the value of using AI to translate samples, he emphasizes that he would never condone translating an entire book using a machine. The key to the heart of translation is “that intimate, subjective relationship between a text and the translator,” he says—the nebulous yet nonetheless living connection that translator Kate Briggs describes as the “uniquely relational, lived-out practice” of “this little art.”

Will Evans, founder of independent publisher Deep Vellum in Dallas, does not see a future in which machine-led translations supersede the human. “I do not believe AI-led translation will be competitive for works of the literary caliber we are interested in any time before the AI bubble bursts,” he says, “though I have no doubts the corporate publishers who are interested in serving the same books to the same readers over and over again will have no such qualms.”

In the realm of literature, there is still a sanctity around “the human and the humane,” as Stavans puts it. “Machines can’t read a book or experience any of the personal connections to language that give a book life,” adds Rogers, who became a translator after translating Finnish song lyrics for friends. “Machines don’t find themselves unexpectedly chuckling at a phrase, or repeating a string of words because its sounds are satisfying, or remembering being in a place like the place described in a book.” Though a cliché, it nevertheless rings true: The destination might pale in comparison to the joy of the journey, something a machine might never know.

Jimin Kang is a Seoul-born, Hong Kong–raised, and England-based journalist and writer. Her work has appeared in the New York Times, the Nation, the Kenyon Review and the Los Angeles Review of Books, among other publications.

[azspot]

The unique opportunity that AI offers humanity is to push back against the process started by computerization — to extend the relevance, reach and value of human expertise to a larger set of workers. Because artificial intelligence can weave information and rules with acquired experience to support decision-making, it can enable a larger set of workers equipped with necessary foundational training to perform higher-stakes decision-making tasks currently arrogated to elite experts, such as doctors, lawyers, software engineers and college professors. In essence, AI — used well — can assist with restoring the middle-skill, middle-class heart of the U.S. labor market that has been hollowed out by automation and globalization.

AI Could Actually Help Rebuild The Middle Class

[datastring]

Propeller and Impeller Mixers Market Set to Reach $1,836.7 Million by 2035 Amid Industrial Expansion

The global Propeller and Impeller Mixers market is on track to grow significantly, with projected revenues increasing from $663.4 million in 2024 to $1,836.7 million by 2035, reflecting an average annual growth rate of 9.7%. This growth is driven by rising demand in critical application areas such as chemical mixing, food processing, wastewater treatment, and oil dispersion, which rely heavily on efficient and reliable mixing technologies.

Detailed Analysis - https://datastringconsulting.com/industry-analysis/propeller-and-impeller-mixers-market-research-report

Key Drivers and Application Areas

Propeller and impeller mixers serve as essential equipment across a diverse range of industries. In chemical processing, these mixers help ensure homogeneity and facilitate complex reactions. The food and beverage sector uses them for consistent texture and quality during blending. In wastewater treatment, they play a pivotal role in sludge mixing and aeration, while in oil and energy applications, they are critical for dispersion and emulsification processes.

As these industries scale production and embrace process automation, the need for technologically advanced mixers is set to grow rapidly. Customization, energy efficiency, and process adaptability are becoming top priorities in product development.

Competitive Landscape and Strategic Direction

The Propeller and Impeller Mixers market is defined by strong competition among prominent manufacturers. Industry leaders such as Sulzer Ltd, Philadelphia Mixing Solutions, Lightnin Mixers (SPX Flow), ProQuip Inc., Silverson Machines Ltd, Xylem Inc., Mixel Company, Chemineer Inc. (NOV Inc.), Alfa Laval, KSB, Brawn Mixer Inc., and Jongia NV are actively investing in innovation to maintain their market edge.

These companies are advancing mixer designs through improved blade geometry, material enhancements, and integration of digital controls. They are also exploring strategic partnerships, acquisitions, and regional expansions to broaden their customer base and access new revenue streams.

Global Expansion and Regional Shifts

North America and Europe continue to lead in market activity due to their mature industrial bases and high investment in process optimization. However, these regions face challenges such as high capital expenditure and evolving regulatory demands, prompting firms to seek growth in emerging markets.

Countries like India, Brazil, and South Africa are gaining attention as next-generation demand hubs. Rising industrial activity, particularly in chemical production and food processing, coupled with improving infrastructure, makes these regions ideal for market entry and expansion.

Evolving Supply Chains and Technological Complexity

The supply chain for Propeller and Impeller Mixers—from raw material sourcing to product design, manufacturing, and distribution—is undergoing transformation. This evolution is being driven by the need for customized solutions, digital integration, and sustainable manufacturing practices. As the market matures, companies are expected to invest in smarter production capabilities, modular mixer designs, and global logistics networks to meet demand efficiently and sustainably.

About DataString Consulting

DataString Consulting delivers comprehensive market research and strategic intelligence services tailored to meet the specific needs of businesses across B2B and B2C domains. With over 30 years of combined industry experience, the firm provides data-driven strategies for TAM expansion, market entry, and revenue diversification. Its unique approach filters market noise into actionable insights, helping clients reduce go-to-market time and unlock high-growth opportunities.

DataString tracks more than 15 major industries and 60 sub-sectors, ensuring continuous coverage of emerging trends and competitive dynamics. Whether you're targeting a niche market or expanding globally, DataString provides the intelligence needed to succeed.

[educationmore]

Python for Beginners: Launch Your Tech Career with Coding Skills

Are you ready to launch your tech career but don’t know where to start? Learning Python is one of the best ways to break into the world of technology—even if you have zero coding experience.

In this guide, we’ll explore how Python for beginners can be your gateway to a rewarding career in software development, data science, automation, and more.

Why Python Is the Perfect Language for Beginners

Python has become the go-to programming language for beginners and professionals alike—and for good reason:

Simple syntax: Python reads like plain English, making it easy to learn.

High demand: Industries spanning the spectrum are actively seeking Python developers to fuel their technological advancements.

Versatile applications: Python's versatility shines as it powers everything from crafting websites to driving artificial intelligence and dissecting data.

Whether you want to become a software developer, data analyst, or AI engineer, Python lays the foundation.

What Can You Do With Python?

Python is not just a beginner language—it’s a career-building tool. Here are just a few career paths where Python is essential:

Web Development: Frameworks like Django and Flask make it easy to build powerful web applications. You can even enroll in a Python Course in Kochi to gain hands-on experience with real-world web projects.

Data Science & Analytics: For professionals tackling data analysis and visualization, the Python ecosystem, featuring powerhouses like Pandas, NumPy, and Matplotlib, sets the benchmark.

Machine Learning & AI: Spearheading advancements in artificial intelligence development, Python boasts powerful tools such as TensorFlow and scikit-learn.

Automation & Scripting: Simple yet effective Python scripts offer a pathway to amplified efficiency by automating routine workflows.

Cybersecurity & Networking: The application of Python is expanding into crucial domains such as ethical hacking, penetration testing, and the automation of network processes.

How to Get Started with Python

Starting your Python journey doesn't require a computer science degree. Success hinges on a focused commitment combined with a thoughtfully structured educational approach.

Step 1: Install Python

Download and install Python from python.org. It's free and available for all platforms.

Step 2: Choose an IDE

Use beginner-friendly tools like Thonny, PyCharm, or VS Code to write your code.

Step 3: Learn the Basics

Focus on:

Variables and data types

Conditional statements

Loops

Functions

Lists and dictionaries

If you prefer guided learning, a reputable Python Institute in Kochi can offer structured programs and mentorship to help you grasp core concepts efficiently.

Step 4: Build Projects

Learning by doing is key. Start small:

Build a calculator

Automate file organization

Create a to-do list app

As your skills grow, you can tackle more complex projects like data dashboards or web apps.

How Python Skills Can Boost Your Career

Adding Python to your resume instantly opens up new opportunities. Here's how it helps:

Higher employability: Python is one of the top 3 most in-demand programming languages.

Better salaries: Python developers earn competitive salaries across the globe.

Remote job opportunities: Many Python-related jobs are available remotely, offering flexibility.

Even if you're not aiming to be a full-time developer, Python skills can enhance careers in marketing, finance, research, and product management.

If you're serious about starting a career in tech, learning Python is the smartest first step you can take. It’s beginner-friendly, powerful, and widely used across industries.

Whether you're a student, job switcher, or just curious about programming, Python for beginners can unlock countless career opportunities. Invest time in learning today—and start building the future you want in tech.

Globally recognized as a premier educational hub, DataMites Institute delivers in-depth training programs across the pivotal fields of data science, artificial intelligence, and machine learning. They provide expert-led courses designed for both beginners and professionals aiming to boost their careers.

Python Modules Explained - Different Types and Functions - Python Tutorial

[chandupalle]

Global Process Automation and Instrumentation Market Report: Industry Size, Share, Statistics, Companies, Growth Analysis - 2027

The global process automation and instrumentation industry are experiencing significant growth and evolution driven by technological advancements, increasing demand for operational efficiency, and the need for enhanced safety measures across various sectors.

Process Automation and Instrumentation Industry Overview

The process automation and instrumentation market encompass a wide array of technologies, including control systems, sensors, transmitters, actuators, and software solutions, designed to automate and monitor industrial processes. These technologies find applications across diverse sectors such as oil and gas, chemical, pharmaceuticals, food and beverage, energy, and manufacturing.

Global Process Automation and Instrumentation Market Size:

According to MarketsandMarkets latest market research report, the global process automation and instrumentation market size is projected to reach USD 86.6 billion by 2027, at a CAGR of 5.5% during the forecast period.

Global Process Automation and Instrumentation Market Share:

In terms of region, Asia Pacific led the global process automation and instrumentation market, followed Asia Pacific led the global process automation and instrumentation market, followed by North America and Europe in 2021. In Asia Pacific, the demand for process automation and instrumentation solutions is growing from the oil & gas and food & beverages industries due to the ever-increasing population in Asia Pacific.

Increasing investments in clean energy infrastructure in Asia Pacific to meet escalating demand for electricity and reduce reliance on fossil fuels to generate energy. Also, the process automation and instrumentation market for the pharmaceuticals industry in this region is expected to grow at the highest CAGR from 2022 to 2027 due to changing regulatory environment. Also, advantages such as higher reliability and flexibility and greater speed and accuracy offered by process automation encourage pharma companies to adopt process automation and instrumentation solutions.

Download PDF Brochure: https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=1172

Industrial Cybersecurity Market Growth Analysis:

The process automation and instrumentation industry are poised for significant growth in the coming years, driven by factors such as:

Industry 4.0 Adoption: The fourth industrial revolution, characterized by the integration of digital technologies into manufacturing processes, is driving the adoption of advanced automation and instrumentation solutions.

Focus on Efficiency and Safety: Industries are increasingly focusing on enhancing operational efficiency, reducing downtime, and ensuring safety compliance, which fuels the demand for automation technologies.

Rising Demand in Emerging Economies: The growing industrialization and infrastructural development in emerging economies present lucrative opportunities for market players to expand their presence and tap into new markets.

Top Process Automation and Instrumentation Companies - Key Market Players ABB Ltd. (Switzerland), Emerson Electric Co. (US), Siemens (Germany), General Electric Company (US), and Schneider Electric (France) are a few major players in process automation and instrumentation market.

[carlhofelina]

Lead Generation: Key Strategy for Business Growth

Lead generation attracts and converts in front of your product or service, from where such prospects are guided through a buyer's journey until that sale is secured.

In fact, 67% of companies use lead generation as the primary metric in content creation. Here's why it matters for your business.

Benefits of Lead Generation

● Expand Your Market: Lead generation helps you unlock untapped segments of your audience. This unlocks opportunities for new markets.

● Grow Your Following: Developing valuable content that positions your brand as a source of thought leaders will build a loyal following that is likely to grow into customers and advocates.

● Increase Revenue: Target lead gen means reaching qualified prospects, making conversion easier for your sales teams.

● Improve Lead Quality: Concentrated content and targeting ensures that marketing happens to your desired audience, thereby making the prospects much higher-quality and making conversion more probable.

● Reduce Cold Calls: Hot leads make prospects come to you, making cold calls time-consuming and low probability.

● Automate Lead Management: Use of tools like CRM and email automation makes capturing and nurturing much easier by freeing up crucial time for them.

Beyond traditional marketing, BPO admin support and global solutions add to the quality of lead generation. Data management and customer communication can be outsourced to let you streamline, increase efficiency, and free your team for better core objectives using BPO admin support. Similar to that, global solutions bring scalable tools and platforms, ensuring optimized operations and broader reach in a variety of regions.

Lead generation is the key to sustainable growth. Targeted strategies, campaign refinement, and process automation can enhance conversions, expand reach, and drive long-term success.

Ready to take your business to the next level? Visit Best Virtual Specialist today to discover more ways to boost lead generation and grow your revenue!

Reference: https://www.sendoso.com/demand-generation/benefits-of-lead-generation