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.
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.
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.
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).
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
Shares of Meta surged 15% after the social-media giant defied analysts’ estimates. It posted earnings of $5.33 per share on revenue of $40.11 billion. The company also declared its first-ever dividend payment. Share buy-back was also announced.
Meta platforms Inc. One year chart
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
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 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.
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.
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.
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.
Robot chatting to human chatbot online
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.
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.
