Big tech Archives - Taking Stock

August 28, 2025September 12, 2025

AI In, Jobs Out: The Great Hiring Slowdown

Has BIG tech and AI stopped hiring? Not quite, though the hiring landscape has definitely shifted gears. Here’s the current take…

🧠 AI Hiring: Still Hot, Just More Focused

Private AI firms like OpenAI, Anthropic, and Perplexity are still hiring aggressively, especially for Machine Learning Engineers and Enterprise Sales roles. These two categories alone account for thousands of openings.
Even legacy tech giants like Salesforce are scaling up AI-focused sales teams—Marc Benioff announced 2,000 new hires just to sell AI solutions.
The demand for ML Engineers has splintered into niche specializations like LLM fine-tuning, inference optimisation, and RAG infrastructure, showing how deep the rabbit hole goes.

🖥️ Big Tech: Cooling, Not Collapsing

Across the U.S., software engineering roles dropped from 170,000 in March to under 150,000 by July.
AI job postings fell from 80,000 in February to just over 50,000 in June, though July showed a slight rebound.
Despite the slowdown, AI still makes up 11–15% of all software roles, suggesting it’s a strategic priority even as overall hiring cools.

🌍 Beyond Silicon Valley

States like South Dakota and Connecticut are seeing surprising growth in AI job postings—South Dakota reportedly jumped 164% last month.
The hiring boom is expanding into non-traditional industries, not just Big Tech. Think biotech, retail, and even energy sectors integrating AI.

So while the hiring frenzy of 2023 has mellowed, AI talent remains a hot commodity—just more targeted and strategic.

The general reporting across August 2025 paints a clear picture of slower, more cautious hiring, especially in tech and AI-adjacent roles.

🧊 Hiring Has Cooled—Especially for AI-Exposed Roles

In the UK, tech and finance job listings fell 38%, nearly double the broader market decline.
Entry-level roles and those involving repetitive tasks (like document review or meeting summarisation) are increasingly at risk of automation.
Even in sectors with strong business performance, such as IT and professional services, job opportunities have continued to shrink.

🧠 AI’s Paradox: High Usage, Low Maturity

McKinsey reportedly says that while 80% of large firms use AI, only 1% say their efforts are mature, and just 20% report enterprise-level earnings impact.
Most AI deployments are still horizontal (chatbots, copilots), while vertical use cases (full process automation) remain stuck in pilot mode.

Infographic of AI effect on jobs and hiring

📉 Broader Market Signals

Job adverts have dropped most for occupations most exposed to AI, especially among young graduates.
Despite a slight uptick in hiring intentions in June and July, the overall labour market shows a marked cooling.

So yes, the general tone is one of strategic hesitation—companies are integrating AI but not rushing to hire unless the role is future-proofed.

AI In, Jobs Out: The Great Hiring Slowdown

It’s official: the AI revolution has arrived—but the job listings didn’t get the memo.

Across the UK and U.S., tech hiring has slowed to a cautious crawl. Once-bustling boards now resemble digital ghost towns, especially for roles most exposed to automation.

Software engineering vacancies dropped by over 20% in just four months, while AI-related postings—once the darlings of 2023—have cooled from 80,000 to barely 50,000.

The irony? AI adoption is booming. Over 80% of large firms now deploy some form of artificial intelligence, from chatbots to copilots.

Yet only 1% claim their efforts are ‘mature’, and fewer still report meaningful earnings impact. It’s a paradox: widespread usage, minimal payoff, and a hiring freeze to match.

Even in sectors with strong performance—IT, finance, professional services—the job market is shrinking. Graduates face a particularly frosty reception, as entry-level roles vanish into the algorithmic ether.

Meanwhile, AI firms themselves are hiring with surgical precision: machine learning engineers and enterprise sales reps remain in demand, but the days of blanket recruitment are over.

Geographically, the hiring map is shifting too. South Dakota saw a 164% spike in AI job postings last month, while London and San Francisco quietly tightened their belts.

So, AI isn’t killing jobs—it’s reshaping them. The new roles demand fluency in automation, compliance, and creative problem-solving.

The rest? They’re being quietly retired.

For now, the job market belongs to the adaptable, the analytical, and the algorithmically literate.

Everyone else may need to reboot, eventually, but not quite just yet.

August 22, 2025September 12, 2025

U.S. zombie companies on the rise!

As BIG tech poaches top AI talent, these companies are stripped to the bone as the tech talent is being hollowed out!

In the race to dominate artificial intelligence, America’s tech giants are vacuuming up talent at an unprecedented pace.

But behind the headlines of billion-dollar acquisitions and flashy AI demos lies a quieter crisis. The creation of ‘zombie companies’ — startups left staggering and soulless after their brightest minds are poached by Big Tech.

These zombie firms aren’t dead, but they’re no longer truly alive either. They continue to operate, maintain websites, and pitch to investors, yet their core innovation engine has stalled. The problem isn’t just brain drain — it’s brain decapitation.

When a startup loses its founding engineers, lead researchers, or visionary product designers to the likes of Google, Meta, or Microsoft, what remains is often a shell with no clear path forward.

The allure is understandable. Big Tech offers salaries that dwarf startup equity, access to massive compute resources, and the prestige of working on frontier models. But the downstream effect is corrosive.

Startups, once the lifeblood of AI experimentation, are now struggling to retain talent long enough to reach product maturity. Some pivot to consultancy, others limp along with outsourced development, and many quietly fold — their IP absorbed, their vision diluted.

This phenomenon is particularly acute in the U.S., where venture capital encourages rapid scaling but rarely protects against talent attrition. The result is a growing class of companies that exist more for optics than output — kept alive by inertia, legacy funding, or the hope of acquisition.

They clutter the innovation landscape, making it harder for truly disruptive ideas to gain traction.

Ironically, Big Tech’s hunger for talent may be undermining the very ecosystem it depends on. By stripping startups of their creative lifeblood, it risks turning the AI sector into a monoculture. This culture is then dominated by a few players, with fewer voices and less diversity of thought.

The solution isn’t simple. It may require new funding models, stronger incentives for retention, or even regulatory scrutiny of talent acquisition practices.

But one thing is clear: if the U.S. wants to remain the global leader in AI, it must find a way to nurture its startups — not just harvest them.

Otherwise, the future of innovation may be haunted by the walking dead.

July 29, 2025September 12, 2025

Are investors saying it’s time to move on from tariffs and if so to what effect on the markets?

It looks like investor sentiment is shifting away from obsessing over tariffs—though not because they’ve disappeared.

Instead, there’s a growing sense that tariffs may be settling into a predictable range, especially in the U.S., where President Trump signalled a blanket rate of 15–20% for countries lacking specific trade agreements.

Here’s how that’s playing out

🌐 Why Investors Are Moving On

Predictability over Panic: With clearer expectations around tariff levels, markets may no longer treat them as wildcards.
Muted Market Reaction: The recent U.S.-EU trade deal barely nudged the S&P 500 or European indexes after moving the futures initially, signalling tariffs aren’t the hot trigger they once were.
Economists Cooling Expectations: Revisions to tariff impact estimates suggest future trade deals might not generate outsized optimism on Wall Street.

📈 Effects on the Markets

Focus Shift: Investors are turning to earnings—particularly from the ‘Magnificent Seven’ tech giants—and macroeconomic data for momentum.
Cautious Optimism: While stocks haven’t rallied hard, they’re not dropping either. Traders seem to be waiting for a new catalyst, like U.S. consumer strength or signs of a bull phase in certain indexes.
Geopolitical Undercurrents: A new deadline for Russia to reach a peace deal and threats of ‘secondary tariffs’ could still stir volatility, depending on how global partners react.

So, in short tariffs aren’t gone, but they’ve become background noise. Investors are tuning in to the next big signals.

If you’re keeping an eye on retail, tech earnings, or commodity flows, this shift could have ripple effects worth dissecting.

Market moving events, other than tariffs

Date	Event/Catalyst	Market Impact Potential
July 30	Meta earnings + possible stock split	📈 High (tech sentiment)
July 31	Fed meeting	📈📉 High (rate guidance)
Aug 1	U.S.–EU tariff milestone, not flashpoint	📉 Moderate (sector recalibration)
July 22	U.S. AI Action Plan (released)	📈 Unclear (dependent on execution

March 26, 2025September 12, 2025

China’s position on open-source artificial intelligence (AI) is upending the global AI race

China’s embrace of open-source artificial intelligence (AI) is revolutionising the global AI landscape, challenging traditional notions of innovation and competitiveness in this rapidly evolving field.

Traditionally, the AI sector has been dominated by proprietary models and closed-source systems, particularly in the U.S.

However, China has made a strategic pivot towards open-source initiatives, driven by trailblazers like the AI startup DeepSeek.

DeepSeek’s R1 model, released earlier this year, has become a symbol of China’s open-source movement. Distributed under the permissive MIT licence, the R1 model allows unrestricted use, modification and distribution.

This approach has disrupted traditional business models by democratising access to cutting-edge AI tools. Companies from tech giants like Baidu and Tencent to emerging players like ManusAI have followed suit, releasing their own open-source models and fostering a collaborative environment for AI innovation.

This shift is seen by some as China’s ‘Android moment’ in AI – a reference to the impact of Google’s open-source Android operating system on the mobile app ecosystem.

The move towards open-source has enabled rapid cost reductions, increased accessibility, and accelerated product development. Chinese firms have leveraged these advantages to narrow the perceived technological gap with the U.S., with some analysts suggesting that the disparity has shrunk from years to mere months.

Despite these advancements, the open-source approach also raises questions about intellectual property, security, and sustainable business models.

While it has catalysed innovation, it remains to be seen whether open-source strategies can sustain long-term competitiveness against well-funded proprietary systems.

China’s open-source embrace exemplifies a bold shift in AI strategy, emphasizing collaboration and accessibility over exclusivity.

This paradigm shift could redefine global dynamics in artificial intelligence, fostering a more inclusive and innovative future for the industry.

January 27, 2025September 12, 2025

China’s DeepSeek low-cost challenger to AI rattles tech U.S. markets

U.S. technology stocks plunged as Chinese startup DeepSeek sparked concerns over competitiveness in AI and America’s lead in the sector, triggering a global sell-off

DeepSeek launched a free, open-source large-language model in late December 2024, claiming it was developed in just two months at a cost of under $6 million.

The developments have stoked concerns about the large amounts of money big tech companies have been investing in AI models and data centres.

DeepSeek is a Chinese artificial intelligence startup that has recently gained significant attention in the AI world. Founded in 2023 by Liang Wenfeng, DeepSeek develops open-source large language models. The company is funded by High-Flyer, a hedge fund also founded by Wenfeng.

The AI models from DeepSeek have demonstrated impressive performance, rivaling some of the best chatbots in the world at a fraction of the cost. This has caused quite a stir in the tech industry, leading to significant drops in the stock prices of major AI-related firms.

The company’s latest model, DeepSeek-V3, is known for its efficiency and high performance across various benchmarks.

DeepSeek’s emergence challenges the notion that massive capital expenditure is necessary to achieve top-tier AI performance.

The company’s success has led to a re-evaluation of the AI market and has put pressure on other tech giants to innovate and reduce costs.

October 16, 2024September 12, 2025

Big tech companies are increasingly adopting nuclear power to meet the high energy demands of their AI data centres

Why?

Elevated Energy Needs

AI systems, particularly generative AI, necessitate substantial computational power, leading to significant energy use. Conventional energy sources might not meet these growing demands.

Environmental Commitments

Numerous tech firms have pledged to lower their carbon emissions. Nuclear power, a low-emission energy source, supports these environmental commitments.

Dependability

Nuclear energy offers a consistent and uninterrupted power supply, essential for data centres that operate around the clock.

Technological Advancements

Progress in nuclear technologies, such as small modular reactors (SMRs), has enhanced the feasibility and appeal of nuclear power for extensive use.

For example, Google has entered into an agreement with Kairos Power for electricity from small modular reactors to bolster its AI operations. In a similar vein, Microsoft has collaborated with Constellation to refurbish an inactive reactor at the Three Mile Island nuclear facility.

These collaborations mark a notable transition in the energy strategies of the tech sector, as they pursue dependable, eco-friendly, and robust power solutions to support their AI initiatives.

August 29, 2024September 12, 2025

Nvidia reports 122% revenue growth

Nvidia has announced earnings surpassing Wall Street forecasts and has issued guidance for the current quarter that exceeds expectations.

As the artificial intelligence boom continues, Nvidia remains a major beneficiary. Despite a stock price dip, after trading hours, the stock has risen approximately 150% this year. The question remains whether Nvidia can sustain this growth trajectory.

Nvidia said it expects about $32.5 billion in current-quarter revenue, versus $31.7 billion expected by analysts, according to analysis That would be an increase of 80% from a year earlier.

Revenue continues to surge, rising 122% on an annual basis during the quarter, following three straight periods of year-on-year growth in excess of 200%.

Nvidia’s data centre business, which encompasses its AI processors, saw a 154% increase in revenue from the previous year, reaching $26.3 billion and representing 88% of the company’s total sales.

However, not all these sales were from AI chips. Nvidia reported that its networking products contributed $3.7 billion in revenue.

The company primarily serves a select group of cloud service providers and consumer internet firms, including Microsoft, Alphabet, Meta, and Tesla. Nvidia’s chips, notably the H100 and H200, are integral to the majority of generative AI applications, like OpenAI‘s ChatGPT.

Nvidia also announced a $50 billion stock buyback.

Nvidia shares dropped close to 5% in after-hours pre-market trade (29th August 2024).

February 2, 2024September 12, 2025

Happy days on Wall Street for BIG tech companies

It was a good day of earnings for Big Tech companies.

Three of the Magnificent 7 results dominated the headlines: Meta, Amazon and Apple. Nasdaq and S&P 500 gained in ‘after the bell’ trading. This after a punishing day for Alphabet and Microsoft, despite good results.

Nasdaq 100 closed at: 17344 but climbed above 17500 in after-hours trading.

Wall Street seemed impressed with Meta’s results.

Meta platforms Inc. One year chart

The results show Meta’s online ad business continues to recover well from a terrible 2022.
Sales in the Q4 jumped 25% year on year.
Expenses decreased 8% year over year to $23.73 billion.

Amazon

Investors also enjoyed Amazon’s earnings, which easily topped Wall Street’s predictions. The ecommerce giant also provided a strong positive outlook. The stock jumped 7% in extended trading.

Amazon.com Inc. One year chart

Q4 was a record-breaking Holiday shopping season in the U.S. and closed out a robust 2023 for Amazon. Amazon has much planned for 2024.

Apple

But Apple didn’t benefit from the same treatment despite posting strong results.

Apple Inc. One year chart

Apple also exceeded estimates, reporting revenue growth for the first time in a year. But shares slid more than 2% in extending trading after it posted a 13% decline in sales in China.

Apple’s outlook suggesting weak iPhones sales may have also disappointed investors.

December 6, 2023September 12, 2025

Is there a water crisis looming and could BIG Tech make things worse?

Water is a precious Earth resource. It is becoming increasingly scarce due to climate change, population growth, pollution and waste. Without water we are nothing.

According to some sources, Big Tech and AI are contributing to the water crisis by using large amounts of water to cool their data systems and AI computations.

Researchers estimate that Microsoft used 1.7 billion gallons of water for AI alone in 2022, a 34% increase from 2021. Google also reported a 20% increase in water usage, mostly due to its AI work. One of the most water-intensive AI models is ChatGPT, which is estimated to use half a litre of water for every series of prompts.

These numbers are alarming, considering that water is a finite and vital resource for humans and ecosystems.

ChatGPT is estimated to use the equivalent of one 16-ounce bottle of water (approx’ half a litre) for every 20-50 queries according to a study by Shaolei Ren, an associate professor of electrical and computer engineering at the University of California.

BIG Tech aware of environmental impact

Some tech companies are aware of the environmental impact of their AI activities and are trying to find ways to reduce their water consumption and carbon footprint. For example, Microsoft has pledged to become water positive, carbon negative, and waste-free by 2030.

**Is there a water crisis looming and could BIG Tech make things worse?**

Google has also set a goal to operate on 24/7 carbon-free energy by 2030. OpenAI, the creator of ChatGPT, has stated that it is working on improving the efficiency of its AI models. Some possible solutions include using renewable energy sources, developing better algorithms and hardware, and locating data centres in colder climates.

Too much

Some argue that Big Tech and AI are using too much water, and that they should be regulated. They should be held accountable for their environmental impact.

Others may contend that Big Tech and AI are providing valuable services and innovations and they are taking steps to mitigate their water usage and become more sustainable.

Chatbots and AI share a thirst for water

November 23, 2023September 12, 2025

Some tech executives think AI is giving Big Tech ‘inordinate’ power!

Too much power for too few

Tech execs have expressed concern that the development of artificial intelligence (AI) is concentrated in the hands of too few companies, potentially giving them too much power. OpenAI’s ChatGPT marked the start of what many in the industry have called an AI arms race, as tech giants including Microsoft and Google have sought to develop and launch AI models.

A number of tech execs have said that they feel users have lost control of their data online and that it is being harnessed by technology giants to feed their profits.

The development of artificial intelligence (AI) is concentrated in the hands of too few companies, potentially giving them excessive control over the rapidly evolving technology.

OpenAI’s ChatGPT

An explosion of interest in AI was sparked by OpenAI’s ChatGPT late last year thanks to the novel way in which the chatbot can answer user prompts. Its popularity contributed to the start of what many in the tech industry have called an AI arms race, as tech giants including Microsoft and Google seek to develop and launch their own artificial intelligence models. These require huge amounts of computing power as they are trained on massive amounts of data.

Meredith Whittaker reportedly said of large tech companies and the current deployment of AI…

‘Right now, there are only a handful of companies with the resources needed to create these large-scale AI models and deploy them at scale. And we need to recognize that this is giving them inordinate power over our lives and institutions’, Meredith Whittaker, president of encrypted messaging app Signal, is reported to have said. ‘We should really be concerned about, again, a handful of corporations driven by profit and shareholder returns making such socially consequential decisions’.

Whittaker previously spent 13 years at Google but became disillusioned in 2017 when she found out the search giant was working on a controversial contract with the Department of Defence known as Project Maven. Whittaker grew concerned Google’s AI could potentially be used for drone warfare and helped organize a walkout at the company that involved thousands of employees.

‘AI, as we understand it today, is fundamentally a technology that is derivative of centralized corporate power and control’, Whittaker reportedly said. ‘It is built on the concentrated resources that accrued to a handful of large tech corporations, largely based in the U.S. and China via the surveillance advertising business model, which gave them powerful computational infrastructure and huge amounts of data; large markets from which to pull that data; and the ability to process and structure that data in ways useful for creating new technologies.’

In essence, BIG TECH has far too much power in AI technology.

Tim Berners-Lee

The inventor of the web, Tim Berners-Lee, has also raised concerns about the concentration of power among the tech giants. Jimmy Wales, the founder of Wikipedia, says it is the state of social media that is of particular concern right now. On AI, however, he feels that while the technology giants now are leading the way, there is space for disruption.

Big tech and social media giants are inflicting profound damage on our society, and he believes AI could make this worse.

October 24, 2023September 12, 2025

Apple playing catch-up in AI boom

Apple and generative AI technology is a topic that has been generating a lot of interest and speculation lately.

According to various reports, Apple is working on developing its own large language model and chatbot, which could potentially enhance its products and services with new features and capabilities. However, some analysts and experts have also raised questions about whether Apple has missed an opportunity to be a leader in the generative AI field, as it seems to be lagging behind its competitors such as Google, Microsoft, and OpenAI.

Apple uses AI in its products but hasn’t launched a generative AI product along the lines of OpenAI’s ChatGPT or Google Bard. Instead, Apple’s AI is used for improving photos and autocorrecting text.

$1 billion per year plan

Apple is on track to spend $1 billion per year on developing its generative artificial intelligence products, Bloomberg reported.
Apple is looking to use AI to improve Siri, Messages and Apple Music.
The spending comes as the company plays catch-up to some competitors who have already debuted new AI products and features, such as Google, Microsoft and Amazon.
Apple was caught flat-footed when ChatGPT and other AI tools took the technology industry by storm.

Generative AI

Generative AI is a subfield of artificial intelligence that focuses on creating content such as text, images, videos, music, and more, based on data and algorithms. One of the most popular examples of generative AI is ChatGPT, a chatbot that can respond to questions and other prompts in a natural and human-like way.

Watercolour artwork impression – ChatGPT was released by OpenAI in 2022, and since then, it has been widely used and improved by various companies and researchers.

ChatGPT was released by OpenAI in 2022, and since then, it has been widely used and improved by various companies and researchers.

Apple slow response

Apple, on the other hand, has been relatively quiet about its generative AI efforts, until recently. In October 2023, Bloomberg reported that Apple was internally testing a ‘ChatGPT-like’ chatbot nicknamed ‘Apple GPT’, but it had not devised a clear strategy for releasing generative AI tools to the public. Apple’s CEO Tim Cook also confirmed that the company was working on generative AI for years, but it was approaching it ‘really thoughtfully and think about it deeply’ because of the potential risks and challenges.

Potential challenges Apple faces in developing and deploying generative AI

Privacy

Apple has always been more cautious than its competitors in handling user data, and it has built its reputation on being a privacy-focused company. However, generative AI requires a lot of data to train and improve its models, which could pose a dilemma for Apple. How can it balance the need for data with the respect for user privacy? How can it ensure that its generative AI does not leak or misuse personal information?

Design

Apple is known for its elegant and intuitive design philosophy, which applies to both its hardware and software products. However, generative AI is a complex and unpredictable technology, which could challenge Apple’s design principles. How can it make its generative AI features easy to use and understand for its customers? How can it avoid confusing or misleading users with its generative AI outputs?

Ethics

Apple has always been mindful of the social and ethical implications of its products, and it has often taken a stance on issues such as human rights, environmental sustainability, and diversity. However, generative AI could raise new ethical concerns, such as bias, misinformation and manipulation. But then that is a common problem for all generative AI systems.

Generative AI could raise new ethical concerns, such as bias, misinformation and manipulation.

These are some of the questions that Apple needs to answer before it can launch its generative AI products to the public. It is possible that Apple is taking its time to address these issues carefully and thoroughly, as it has done in the past with other technologies such as Face ID or Apple Pay. However, it is also possible that Apple has missed an opportunity to be a pioneer in the generative AI field, as it has done in the past with other technologies such as smart speakers or cloud computing.

While Apple is working on its generative AI projects internally, its competitors are already offering generative AI.

Google

Google has integrated its large language model LaMDA into various products and services, such as Google Assistant, Google Photos, Google Docs, Google Translate etc. LaMDA can generate natural and conversational responses to any query or prompt, as well as create images and videos based on text descriptions.

Microsoft

Microsoft has acquired OpenAI’s ChatGPT technology and made it available through its Azure cloud platform. ChatGPT can be used by developers and businesses to create chatbots, voice assistants, content generators, and more. Microsoft has also integrated ChatGPT into some of its products such as Outlook, Teams, PowerPoint, and more.

Amazon

Amazon has launched Alexa Conversations, a feature that allows Alexa users to have more natural and engaging conversations with the voice assistant. Alexa Conversations can also leverage Amazon’s vast e-commerce data to provide personalized recommendations and suggestions to users.

These are just some examples of how generative AI is being used by Apple’s competitors.

Apple has missed an opportunity to be a leader in the generative AI field by being too slow or too cautious in developing and deploying its own generative AI products.

However, it is highly likely that Apple is waiting for the right moment to surprise everyone with its innovative and unique generative AI features that will set it apart from its competitors.

Time will tell.

October 16, 2023September 12, 2025

Global electricity energy demanded by BIG tech

Many large tech companies are planning to create their own energy supply or source power from 100% renewable generators.

This is mainly because they have high electricity consumption, especially for their data centres, and they want to reduce their carbon footprint and achieve net-zero emissions targets.

BIG tech companies that are generating their own energy or investing in renewable energy projects

Estimated current electricity demand

The global electricity energy demand is the amount of electricity that the world needs in a given day. It can be calculated by multiplying the average global electricity demand in GW by 24 hours. According to the International Energy Agency (IEA), the average global electricity demand in 2020 was about 3 TW or 3 000 GW. This means that the global electricity energy demand in 2020 was about 72000 GWh or 72 TWh per day.

BIG tech companies are generating their own energy or investing in renewable energy projects – how green is it really?

However, this is an average value, and the actual demand may vary depending on the season, time of day, weather, and other factors.

Energy requirement

The global electricity energy demand is expected to increase in the future, as population grows and living standards improve. The IEA projects that the average global electricity demand will reach 3.8 TW or 3 800 GW by 2030 and 5.2 TW or 5 200 GW by 2050 in the Announced Pledges Scenario, which reflects the full implementation of net-zero emissions targets by some countries and regions. This implies that the global electricity energy demand will reach 91 200 GWh or 91.2 TWh per day by 2030 and 124 800 GWh or 124.8 TWh per day by 2050.

Energy sources to change

The sources of electricity generation will also change in the future, as renewable technologies such as solar PV and wind become more dominant and coal use declines. The IEA reports that the main sources of electricity generation in 2020 were coal (34%), natural gas (23%), hydropower (16%), nuclear (10%), wind (8%), solar PV (4%), biofuels and waste (3%), and other renewables (2%). In the Announced Pledges Scenario, renewables in electricity generation rise from 28% in 2021 to about 50% by 2030 and 80% by 2050.

The world counts.

September 28, 2023September 12, 2025

Luddites against BIG tech’ – a modern rebellion

What are Luddites?

Luddites were a group of workers who protested against the use of machinery that threatened their livelihoods in the early 19th century in Britain. They were not opposed to technology in general, but to the specific machines that were ‘taking away their livelihoods’.

They attacked factories and smashed machines that were replacing their jobs with cheaper and less skilled labour.

BIG tech Luddite comparison – is AI the latest threat?

Some people have compared the Luddites to the modern movements that resist the effects of Big Tech and artificial intelligence (AI) on workers’ lives. They argue that these technologies are creating a new wave of automation that is displacing workers, eroding their rights, and increasing inequality.

They also point out that the Luddites had the support of a majority of English people and eventually led to changes in the law that improved workers’ conditions.

Progress?

However, others have criticized this comparison as inaccurate or misleading. They claim that the Luddites were not successful in stopping technological progress, and that their actions were violent and destructive.

Technology will create new jobs

They also suggest that the Luddite fallacy, which refers to the belief that technological progress causes mass unemployment, has been proven wrong by history. They contend that technology can create new opportunities and benefits for workers, as long as society adapts and regulates it properly.

The question of whether a new modern Luddite rebellion can rise against Big Tech is not a simple one. It depends on how we define Luddites, how we evaluate the impacts of technology, and how we respond to the challenges and opportunities it presents.