#AI market disruption

[jcmarchi]

DeepSeek AI and the Global Power Shift: Hype or Reality?

New Post has been published on https://thedigitalinsider.com/deepseek-ai-and-the-global-power-shift-hype-or-reality/

DeepSeek AI and the Global Power Shift: Hype or Reality?

Artificial Intelligence (AI) is no longer just a technological breakthrough but a battleground for global power, economic influence, and national security. The U.S. has led the AI revolution for years, with companies like OpenAI, Google DeepMind, and Microsoft leading the way in machine learning. But with China aggressively expanding its investments in AI, a new contender has emerged, sparking debates about the future of global AI dominance.

DeepSeek AI is not an accidental development but a strategic initiative within China’s broader AI ambitions. Developed by a leading Chinese AI research team, DeepSeek AI has emerged as a direct competitor to OpenAI and Google DeepMind, aligning with China’s vision of becoming the world leader in AI by 2030.

According to Kai-Fu Lee, AI investor and former Google China President, China has the data, talent, and government support to overtake the U.S. in AI. “The AI race will not be won by the best technology alone but by the country with the most strategic AI deployment. China is winning that battle,” he argues.

Open-Source Accessibility and Expert Perspectives

One of DeepSeek AI’s most disruptive features is its open-source nature, making AI more accessible than proprietary models like GPT-4. Unlike GPT-4, which requires advanced GPUs, DeepSeek AI runs on less sophisticated hardware, enabling businesses with limited computational resources to adopt AI solutions. Moreover, its open-source accessibility also encourages global developers to contribute to and improve the model, promoting a collaborative AI ecosystem. Furthermore, companies can integrate DeepSeek AI without paying licensing fees, disrupting AI’s traditional business model.

Elon Musk has expressed strong skepticism regarding DeepSeek AI’s claims. While many tech leaders have praised its achievements, Musk questioned the company’s transparency, particularly regarding hardware usage. He dismissed claims that DeepSeek AI had achieved its results with a relatively small number of GPUs, implying that the actual number could be much higher. His criticism aligns with industry experts’ concerns that DeepSeek’s rapid success might be overstated or not fully disclosed. Musk’s stance contrasts with the optimism of figures like Marc Benioff, CEO of Salesforce, who publicly celebrated DeepSeek AI’s recent achievements, particularly its surpassing ChatGPT on the App Store. He emphasized that the actual value of AI lies in data and metadata, suggesting that future advancements will be driven by access to these resources. Benioff described DeepSeek’s success as a significant milestone in AI, highlighting its potential to democratize technology and challenge established players. However, he also referred to DeepSeek as “a precision experiment for now,” indicating a cautious optimism about its long-term impact. This perspective reflects a broader conversation about the evolving dynamics in the AI industry.

Prof. Neil Lawrence, DeepMind Professor of Machine Learning at the University of Cambridge, remarked, “The progress is unsurprising, and I think it’s just the tip of the iceberg regarding the type of innovation we can expect in these models. History shows that big firms struggle to innovate as they scale, and what we’ve seen from many of these big firms is a substitution of compute investment for the intellectual hard work.”

Is the AI Race Tilting in China’s Favor?

China is rapidly advancing in the AI race, particularly with the emergence of DeepSeek AI. China’s 14th Five-Year Plan (2021-2025) prioritizes AI as a strategic frontier industry, reinforcing its ambition to lead globally by 2030. Significant state investments in research, talent acquisition, and industrial applications back this effort. DeepSeek has gained international attention with its recent models, including the DeepSeek-R1, which employs advanced reasoning capabilities and operates under an open-source license.

AI expert Andrew Ng notes that while China’s AI infrastructure is growing quickly, the real test lies in scaling these advancements globally. Additionally, challenges remain in addressing AI governance and ethical concerns, especially as DeepSeek’s open-source approach could reshape how information is processed worldwide.

DeepSeek AI is already impacting the AI industry and the stock market. Reports suggest that DeepSeek AI’s announcement caused a temporary dip in NVIDIA’s stock, a key supplier of AI chips for OpenAI and Google. Microsoft and OpenAI are also reportedly re-evaluating their business models in response to the potential threat posed by open-source AI.

This shift might force U.S. and European AI firms to accelerate their development efforts, with companies increasingly investing in more efficient AI models that balance performance and cost-effectiveness. With DeepSeek AI challenging the current paradigm, businesses are exploring new AI monetization strategies, such as modular AI deployments and cloud-based AI marketplaces.

So, is the AI race tilting in China’s favor? While China’s advancements are undeniably significant and create a compelling narrative of rapid progress, it is essential to remain cautious about labeling it as an outright victory. The AI race is complex and multifaceted, involving technological prowess, ethical considerations, governance frameworks, and global cooperation. As the world watches China’s next moves, the true measure of success will depend on how these advancements are scaled and integrated into a worldwide context, ensuring they benefit humanity as a whole while adhering to ethical standards.

Hype vs. Reality: Assessing DeepSeek AI’s True Impact

DeepSeek AI has gained attention in the AI sector, with many considering it a significant development. Its primary advantage is its efficient use of resources, which could reduce business infrastructure costs. By adopting an open-source approach, it allows for rapid growth and customization. Industries such as finance, healthcare, automation, and cybersecurity could benefit from its capabilities. However, there are still substantial challenges that may limit its global adoption.

While the open-source model is viewed as an advantage, it also presents risks. Open AI models can be misused to spread misinformation, create deepfakes, and manipulate data—issues that have led governments worldwide to implement stricter AI regulations. Additionally, China’s strict content moderation policies may reduce its appeal outside its domestic market. Another challenge is its reliance on China’s semiconductor industry, which faces U.S. sanctions that could restrict its ability to scale AI training infrastructure.

Building trust at an international level is another key challenge for DeepSeek AI. Many Western companies hesitate to adopt Chinese AI technology due to concerns about data privacy and regulatory uncertainties. Unlike established players such as OpenAI, which have explicit revenue models, DeepSeek has yet to define a solid monetization strategy, raising questions about its long-term sustainability. Without international partnerships and strong data governance, its reach may remain primarily within China.

AI companies like OpenAI and Google DeepMind are adjusting their strategies to acknowledge this competition. OpenAI is developing more minor, cost-efficient AI models to remain competitive, while DeepMind focuses on ethical AI practices and enterprise solutions to appeal to businesses.

So, is DeepSeek AI all hype, or does it represent a significant shift in AI development? The reality likely falls somewhere in between. While its notable advancements could influence various industries, its global impact will depend on overcoming regulatory barriers, establishing user trust, and navigating geopolitical challenges. Until then, its role in the AI domain remains uncertain.

The Bottom Line

DeepSeek AI represents a significant step in China’s AI ambitions, challenging Western AI leaders and reshaping the industry. Its open-source approach makes AI more accessible and raises security and governance concerns. While some experts consider it a significant disruptor, others caution against overestimating its long-term impact.

Whether DeepSeek AI truly shifts the global AI balance remains uncertain. Its success will ultimately depend on trust, transparency, and the ability to scale outside China. The AI race is far from settled, and only time will reveal whether DeepSeek is a temporary experiment or a lasting force in artificial intelligence.

[onlinemarketingcash4ublogspotcom]

"The Rise of Virtual Influencers, Gary Vaynerchuk's Take"

In this thought-provoking episode, we explore the future of influencer marketing and the rise of AI influencers. Our discussion delves into how AI is set to revolutionize the industry, rendering traditional human influencers obsolete. Discover how businesses and individuals must adapt to this impending transformation and the profound impact it will have on the market. Don't miss out on this eye-opening conversation!

https://www.onlinemarketingcash4u.blogspot.com

Chapters:

(00:00) I think the influencer industry is going to get massively affected by AI

(00:39) It sounds like companies need to adjust too

[kariniai]

Generative AI: Redefining Boundaries and Propelling Industries Forward

The business landscape is in perpetual flux, demanding constant adaptation and evolution. Organizations must keep pace with change and strategically outmaneuver it to thrive. In this dynamic environment, embracing disruptive technologies like Generative AI becomes not just an option but a necessity.

Beyond Analysis, Lies Creation: A New Frontier of AI

Unlike traditional machine learning, which focuses on analysis and classification, Generative AI ventures into creation. Imagine it as an inexhaustible wellspring of AI-powered creativity, capable of generating entirely new content – text, images, music, or even code. Think of it as AI with imagination, ready to unlock possibilities previously confined to the human mind.

Demystifying the Engine: LLMs, NLP, and the Collaborative Powerhouse

This transformative potential hinges on a collaborative interplay of crucial components. Large Language Models (LLMs) form the backbone of many Generative AI systems, particularly those dealing with text. These AI entities are trained on massive datasets, absorbing the intricacies and nuances of human language. This empowers them to generate realistic and coherent text, translate languages, and craft diverse creative content.

Natural Language Processing (NLP) plays a crucial role in this process. By enabling computers to understand and interpret human language, NLP allows Generative AI models to decipher our instructions and translate them into actionable insights, ultimately guiding the desired output.

Generative AI, LLMs, NLP, and machine learning are not isolated entities but rather interlocking pieces of a much larger puzzle. The process begins with feeding massive amounts of data into LLMs. Machine learning algorithms then analyze this data, unearthing complex patterns and structures. NLP techniques come into play next, enabling the system to glean the context and meaning embedded within user instructions and data inputs. Finally, armed with this comprehensive understanding, the Generative AI model generates new data that aligns with the identified patterns and the intent behind the user input.

The Imperative for Action: Embracing the Generative Future

While Generative AI is still in its early stages, its potential is undeniable. Businesses that seize this opportunity and become early adopters stand to gain a significant first-mover advantage, propelling them to the forefront of their industries and delaying; however, they must catch up as Generative AI disrupts existing processes and redefines market dynamics.

Real-World Examples of the Generative AI Advantage:

Marketing & Advertising: Personalized content creation with 30% higher click-through rates and targeted messaging with 20% increased engagement as seen in companies like Unilever and Netflix.

Research & Development: Accelerating drug discovery and pioneering material science innovations as implemented by Pfizer and Siemens.

Customer Service & Support: Implementing automated chatbots with 25% reduced wait times and personalized product recommendations leading to increased customer satisfaction and sales exemplified by Hilton Hotels and Amazon.

Your Roadmap to Leveraging Generative AI

Embarking on the Generative AI journey requires meticulous planning and strategic execution. The first step involves identifying specific use cases within your organization. Where can Generative AI streamline existing processes or unlock entirely new opportunities? Focusing on targeted areas with the potential for high impact is crucial for maximizing the return on investment.

Experimentation through pilot projects offers an invaluable opportunity to gain firsthand experience, identify potential challenges, and cultivate internal support for wider adoption within the organization. Lastly, selecting the appropriate Generative AI tools requires thoroughly evaluating various platforms, ensuring they seamlessly integrate with existing infrastructure and align with specific business needs and resource constraints.

Identify targeted use cases:

Where can Generative AI improve existing processes or create new opportunities?

Focus on areas with high-impact potential for maximum ROI.

Embrace experimentation:

Run pilot projects to gain experience, identify challenges, and build internal support.

Select the right tools:

Evaluate available platforms for seamless integration with existing infrastructure and alignment with business needs and resources.

Introducing Karini AI: Your Generative AI Ally

At Karini AI, we understand the challenges and complexities of operationalizing Generative AI applications. We are committed to partnering with organizations globally to overcome these hurdles and propel them into the forefront of this transformative technology.

Simplified process: We demystify technical complexities and jargon, making Generative AI accessible to everyone.

Unlocking data potential: We empower you to extract value from your data and foster an environment for creative exploration.

Iterative learning: Our platform allows you to experiment, learn, and refine your AI applications, ensuring successful implementation.

Responsible innovation: Our solutions prioritize security and ethical considerations, guaranteeing responsible and trustworthy applications.

Collaborative expertise: We provide the tools and knowledge you need to navigate the Generative AI landscape with confidence.

Karini AI's platform is engineered to demystify Generative AI, transforming it from a complex, technical endeavor into an accessible, user-friendly revolution that anyone can join. It's designed not just to unlock but to unleash the potential of your data, fostering an ecosystem where imagination and innovation aren't just encouraged but expected.

With our platform, you'll navigate through the Generative AI process with ease—from ideation and experimentation to development and deployment. The journey is iterative, allowing for continuous learning and refinement, culminating in robust applications tailored to your organization's needs.

At the heart of our platform is a commitment to security and ethics. We guide you in implementing robust safeguards that ensure your Generative AI applications are not only innovative but also responsible. By fostering a collaborative environment equipped with advanced tools and expertise, Karini AI empowers you to harness the transformative potential of Generative AI and lead the charge in the new frontier of digital innovation.

The time for change is now. Embrace the Generative Future with Karini AI.

About Karini AI:

Fueled by innovation, we're making the dream of robust Generative AI systems a reality. No longer confined to specialists, Karini.ai empowers non-experts to participate actively in building/testing/deploying Generative AI applications. As the world's first GenAIOps platform, we've democratized GenAI, empowering people to bring their ideas to life – all in one evolutionary platform.

Contact:

Jerome Mendell

(404) 891-0255

sales@karini.ai

[achieveinvestment]

Discover the future of real estate with AI! Explore how artificial intelligence is reshaping the market in this insightful article. Read More....https://achieveinvestmentgroup.com/the-next-big-thing-in-real-estate-how-ai-is-disrupting-the-market/

[mediaguides]

The Future Of SEO: Embracing AI And Chatbots

THE MEDIA GUIDES PRESENT State of the Market The Future Of SEO: Embracing AI And Chatbots The world of Search Engine Optimization (SEO) is experiencing a revolutionary shift, courtesy of Artificial Intelligence (AI) and chatbots. With the advent of AI-powered chatbots like Open AI’s ChatGPT, Microsoft’s CoPilot which it powers and the growing list of competitors like Google’s Gemini, the…

[mytsumarketing]

Digital Disruption vs. Transformation: Adapting to the Shifting Business Landscape

🚀 Embrace the digital revolution! Learn how emerging tech is reshaping marketing strategies. From VR to AI, stay ahead of the game. #DigitalMarketing #TechTrends #Marketing

Ever feel like every click on your social media unveils a new world? In this whirlwind of change, how do we seize these opportunities? The social media landscape is evolving at lightning speed. Each emerging technology bears the potential to revolutionize marketing, spanning realms from gaming to advertising and refined messaging delivery. This change holds the power to reshape the very fabric of…

[batboyblog]

Things Biden and the Democrats did, this week #26

July 5-12 2024

The IRS announced it had managed to collect $1 billion in back taxes from high-wealth tax cheats. The program focused on persons with more than $1 million in yearly income who owned more than $250,000 in unpaid taxes. Thanks to money in Biden's 2022 Inflation Reduction Act the IRS is able to undertake more enforcement against rich tax cheats after years of Republicans cutting the agency's budget, which they hope to do again if they win power again.

The Biden administration announced a $244 million dollar investment in the federal government’s registered apprenticeship program. This marks the largest investment in the program's history with grants going out to 52 programs in 32 states. The President is focused on getting well paying blue collar opportunities to people and more people are taking part in the apprenticeship program than ever before. Republican pledge to cut it, even as employers struggle to find qualified workers.

The Department of Transportation announced the largest single project in the department's history, $11 billion dollars in grants for the The Hudson River Tunnel. Part of the $66 billion the Biden Administration has invested in our rail system the tunnel, the most complex Infrastructure project in the nation would link New York and New Jersey by rail under the Hudson. Once finished it's believed it'll impact 20% of the American economy by improving and speeding connection throughout the Northeast.

The Department of Energy announced $1.7 billion to save auto worker's jobs and convert factories to electronic vehicles. The Biden administration will used the money to save or reopen factories in Michigan, Ohio, Pennsylvania, Georgia, Illinois, Indiana, Maryland, and Virginia and retool them to make electric cars. The project will save 15,000 skilled union worker jobs, and created 2,900 new high-quality jobs.

The Department of Housing and Urban Development reached a settlement with The Appraisal Foundation over racial discrimination. TAF is the organization responsible for setting standards and qualifications for real estate appraisers. The Bureau of Labor Statistics last year found that TAF was 94.7% White and 0.6% Black, making it the least racially diverse of the 800 occupations surveyed. Black and Latino home owners are far more likely to have their houses under valued than whites. Under the settlement with HUD TAF will have to take serious steps to increase diversity and remove structural barriers to diversity.

The Department of Justice disrupted an effort by the Russian government to influence public opinion through AI bots. The DoJ shut down nearly 1,000 twitter accounts that were linked to a Russian Bot farm. The bots used AI technology to not only generate tweets but also AI image faces for profile pictures. The effort seemed focused on boosting support for Russia's war against Ukraine and spread negative stories/impressions about Ukraine.

The Department of Transportation announces $1.5 billion to help local authorities buy made in America buses. 80% of the funding will go toward zero or low-emission technology, a part of the President's goal of reaching zero emissions by 2050. This is part of the $5 billion the DOT has spent over the last 3 years replacing aging buses with new cleaner technology.

President Biden with Canadian Prime Minster Justin Trudeau and Finnish President Alexander Stubb signed a new agreement on the arctic. The new trilateral agreement between the 3 NATO partners, known as the ICE Pact, will boost production of ice breaking ships, the 3 plan to build as many as 90 between them in the coming years. The alliance hopes to be a counter weight to China's current dominance in the ice breaker market and help western allies respond to Russia's aggressive push into the arctic waters.

The Department of Transportation announced $1.1 billion for greater rail safety. The program seeks to, where ever possible, eliminate rail crossings, thus removing the dangers and inconvenience to communities divided by rail lines. It will also help update and improve safety measures at rail crossings.

The Department of the Interior announced $120 million to help tribal communities prepare for climate disasters. This funding is part of half a billion dollars the Biden administration has spent to help tribes build climate resilience, which itself is part of a $50 billion dollar effort to build climate resilience across the nation. This funding will help support drought measures, wildland fire mitigation, community-driven relocation, managed retreat, protect-in-place efforts, and ocean and coastal management.

The USDA announced $100 million in additional funds to help feed low income kids over the summer. Known as "SUN Bucks" or "Summer EBT" the new Biden program grants the families of kids who qualify for free meals at school $120 dollars pre-child for groceries. This comes on top of the traditional SUN Meals program which offers school meals to qualifying children over the summer, as well as the new under President Biden SUN Meals To-Go program which is now offering delivery of meals to low-income children in rural areas. This grant is meant to help local governments build up the Infrastructure to support and distribute SUN Bucks. If fully implemented SUN Bucks could help 30 million kids, but many Republican governors have refused the funding.

USAID announced its giving $100 million to the UN World Food Program to deliver urgently needed food assistance in Gaza. This will bring the total humanitarian aid given by the US to the Palestinian people since the war started in October 2023 to $774 million, the single largest donor nation. President Biden at his press conference last night said that Israel and Hamas have agreed in principle to a ceasefire deal that will end the war and release the hostages. US negotiators are working to close the final gaps between the two sides and end the war.

The Senate confirmed Nancy Maldonado to serve as a Judge on the Seventh Circuit Court of Appeals. Judge Maldonado is the 202nd federal Judge appointed by President Biden to be confirmed. She will the first Latino judge to ever serve on the 7th Circuit which covers Illinois, Indiana, and Wisconsin.

Bonus: At the NATO summit in Washington DC President Biden joined 32 allies in the Ukraine compact. Allies from Japan to Iceland confirmed their support for Ukraine and deepening their commitments to building Ukraine's forces and keeping a free and Democratic Ukraine in the face of Russian aggression. World leaders such as British Prime Minster Keir Starmer, German Chancellor Olaf Scholz, French President Emmanuel Macron, and Ukrainian President Volodymyr Zelenskyy, praised President Biden's experience and leadership during the NATO summit

[jeffsperandeo]

The AI Apocalypse is Here: How to Survive When Machines Can See and Hear!

By Jeff Sperandeo As someone who’s spent years capturing stories through visuals and sounds, the recent announcement by OpenAI about ChatGPT going multi-modal struck a chord with me. The integration of voice and image capabilities into this conversational AI model is not just fascinating; it’s revolutionary. However, it’s clear that this leap forward in technology won’t come without its share of…

[reasonsforhope]

Green energy is in its heyday. 

Renewable energy sources now account for 22% of the nation’s electricity, and solar has skyrocketed eight times over in the last decade. This spring in California, wind, water, and solar power energy sources exceeded expectations, accounting for an average of 61.5 percent of the state's electricity demand across 52 days. 

But green energy has a lithium problem. Lithium batteries control more than 90% of the global grid battery storage market. 

That’s not just cell phones, laptops, electric toothbrushes, and tools. Scooters, e-bikes, hybrids, and electric vehicles all rely on rechargeable lithium batteries to get going. 

Fortunately, this past week, Natron Energy launched its first-ever commercial-scale production of sodium-ion batteries in the U.S. 

“Sodium-ion batteries offer a unique alternative to lithium-ion, with higher power, faster recharge, longer lifecycle and a completely safe and stable chemistry,” said Colin Wessells — Natron Founder and Co-CEO — at the kick-off event in Michigan. 

The new sodium-ion batteries charge and discharge at rates 10 times faster than lithium-ion, with an estimated lifespan of 50,000 cycles.

Wessells said that using sodium as a primary mineral alternative eliminates industry-wide issues of worker negligence, geopolitical disruption, and the “questionable environmental impacts” inextricably linked to lithium mining. 

“The electrification of our economy is dependent on the development and production of new, innovative energy storage solutions,” Wessells said. 

Why are sodium batteries a better alternative to lithium?

The birth and death cycle of lithium is shadowed in environmental destruction. The process of extracting lithium pollutes the water, air, and soil, and when it’s eventually discarded, the flammable batteries are prone to bursting into flames and burning out in landfills. 

There’s also a human cost. Lithium-ion materials like cobalt and nickel are not only harder to source and procure, but their supply chains are also overwhelmingly attributed to hazardous working conditions and child labor law violations. 

Sodium, on the other hand, is estimated to be 1,000 times more abundant in the earth’s crust than lithium. 

“Unlike lithium, sodium can be produced from an abundant material: salt,” engineer Casey Crownhart wrote ​​in the MIT Technology Review. “Because the raw ingredients are cheap and widely available, there’s potential for sodium-ion batteries to be significantly less expensive than their lithium-ion counterparts if more companies start making more of them.”

What will these batteries be used for?

Right now, Natron has its focus set on AI models and data storage centers, which consume hefty amounts of energy. In 2023, the MIT Technology Review reported that one AI model can emit more than 626,00 pounds of carbon dioxide equivalent. 

“We expect our battery solutions will be used to power the explosive growth in data centers used for Artificial Intelligence,” said Wendell Brooks, co-CEO of Natron. 

“With the start of commercial-scale production here in Michigan, we are well-positioned to capitalize on the growing demand for efficient, safe, and reliable battery energy storage.”

The fast-charging energy alternative also has limitless potential on a consumer level, and Natron is eying telecommunications and EV fast-charging once it begins servicing AI data storage centers in June. 

On a larger scale, sodium-ion batteries could radically change the manufacturing and production sectors — from housing energy to lower electricity costs in warehouses, to charging backup stations and powering electric vehicles, trucks, forklifts, and so on. 

“I founded Natron because we saw climate change as the defining problem of our time,” Wessells said. “We believe batteries have a role to play.”

-via GoodGoodGood, May 3, 2024

--

Note: I wanted to make sure this was legit (scientifically and in general), and I'm happy to report that it really is! x, x, x, x

[onlinemarketingcash4ublogspotcom]

In this thought-provoking episode, we explore the future of influencer marketing and the rise of AI influencers. Our discussion delves into how AI is set to revolutionize the industry, rendering traditional human influencers obsolete. Discover how businesses and individuals must adapt to this impending transformation and the profound impact it will have on the market. Don't miss out on this eye-opening conversation!

In the rapidly evolving world of marketing, a new player is set to take center stage: AI influencers. This episode explores the profound impact AI technology will have on the influencer industry, potentially rendering traditional human influencers obsolete. The conversation highlights how AI-driven personalities, with their ability to mimic human behavior and engage with audiences, are poised to revolutionize marketing strategies for businesses worldwide.

We delve into the economic implications of this shift, noting that AI influencers will offer a cost-effective alternative to human influencers. With the ability to generate content and engage followers at a fraction of the cost, AI influencers present a lucrative opportunity for businesses looking to maximize their marketing budgets.

[sayruq]

Meta identifies networks pushing deceptive content likely generated by AI

Meta (META.O) said on Wednesday it had found "likely AI-generated" content used deceptively on its Facebook and Instagram platforms, including comments praising Israel's handling of the war in Gaza published below posts from global news organizations and U.S. lawmakers. The social media company, in a quarterly security report, said the accounts posed as Jewish students, African Americans and other concerned citizens, targeting audiences in the United States and Canada. It attributed the campaign to Tel Aviv-based political marketing firm STOIC. While Meta has found basic profile photos generated by artificial intelligence in influence operations since 2019, the report is the first to disclose the use of text-based generative AI technology since it emerged in late 2022. Researchers have fretted that generative AI, which can quickly and cheaply produce human-like text, imagery and audio, could lead to more effective disinformation campaigns and sway elections. In a press call, Meta security executives said they removed the Israeli campaign early and did not think novel AI technologies had impeded their ability to disrupt influence networks, which are coordinated attempts to push messages.

[mostlysignssomeportents]

Big Tech disrupted disruption

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2024/02/08/permanent-overlords/#republicans-want-to-defund-the-police

Before "disruption" turned into a punchline, it was a genuinely exciting idea. Using technology, we could connect people to one another and allow them to collaborate, share, and cooperate to make great things happen.

It's easy (and valid) to dismiss the "disruption" of Uber, which "disrupted" taxis and transit by losing $31b worth of Saudi royal money in a bid to collapse the world's rival transportation system, while quietly promising its investors that it would someday have pricing power as a monopoly, and would attain profit through price-gouging and wage-theft.

Uber's disruption story was wreathed in bullshit: lies about the "independence" of its drivers, about the imminence of self-driving taxis, about the impact that replacing buses and subways with millions of circling, empty cars would have on traffic congestion. There were and are plenty of problems with traditional taxis and transit, but Uber magnified these problems, under cover of "disrupting" them away.

But there are other feats of high-tech disruption that were and are genuinely transformative – Wikipedia, GNU/Linux, RSS, and more. These disruptive technologies altered the balance of power between powerful institutions and the businesses, communities and individuals they dominated, in ways that have proven both beneficial and durable.

When we speak of commercial disruption today, we usually mean a tech company disrupting a non-tech company. Tinder disrupts singles bars. Netflix disrupts Blockbuster. Airbnb disrupts Marriott.

But the history of "disruption" features far more examples of tech companies disrupting other tech companies: DEC disrupts IBM. Netscape disrupts Microsoft. Google disrupts Yahoo. Nokia disrupts Kodak, sure – but then Apple disrupts Nokia. It's only natural that the businesses most vulnerable to digital disruption are other digital businesses.

And yet…disruption is nowhere to be seen when it comes to the tech sector itself. Five giant companies have been running the show for more than a decade. A couple of these companies (Apple, Microsoft) are Gen-Xers, having been born in the 70s, then there's a couple of Millennials (Amazon, Google), and that one Gen-Z kid (Facebook). Big Tech shows no sign of being disrupted, despite the continuous enshittification of their core products and services. How can this be? Has Big Tech disrupted disruption itself?

That's the contention of "Coopting Disruption," a new paper from two law profs: Mark Lemley (Stanford) and Matthew Wansley (Yeshiva U):

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4713845

The paper opens with a review of the literature on disruption. Big companies have some major advantages: they've got people and infrastructure they can leverage to bring new products to market more cheaply than startups. They've got existing relationships with suppliers, distributors and customers. People trust them.

Diversified, monopolistic companies are also able to capture "involuntary spillovers": when Google spends money on AI for image recognition, it can improve Google Photos, YouTube, Android, Search, Maps and many other products. A startup with just one product can't capitalize on these spillovers in the same way, so it doesn't have the same incentives to spend big on R&D.

Finally, big companies have access to cheap money. They get better credit terms from lenders, they can float bonds, they can tap the public markets, or just spend their own profits on R&D. They can also afford to take a long view, because they're not tied to VCs whose funds turn over every 5-10 years. Big companies get cheap money, play a long game, pay less to innovate and get more out of innovation.

But those advantages are swamped by the disadvantages of incumbency, all the various curses of bigness. Take Arrow's "replacement effect": new companies that compete with incumbents drive down the incumbents' prices and tempt their customers away. But an incumbent that buys a disruptive new company can just shut it down, and whittle down its ideas to "sustaining innovation" (small improvements to existing products), killing "disruptive innovation" (major changes that make the existing products obsolete).

Arrow's Replacement Effect also comes into play before a new product even exists. An incumbent that allows a rival to do R&D that would eventually disrupt its product is at risk; but if the incumbent buys this pre-product, R&D-heavy startup, it can turn the research to sustaining innovation and defund any disruptive innovation.

Arrow asks us to look at the innovation question from the point of view of the company as a whole. Clayton Christensen's "Innovator's Dilemma" looks at the motivations of individual decision-makers in large, successful companies. These individuals don't want to disrupt their own business, because that will render some part of their own company obsolete (perhaps their own division!). They also don't want to radically change their customers' businesses, because those customers would also face negative effects from disruption.

A startup, by contrast, has no existing successful divisions and no giant customers to safeguard. They have nothing to lose and everything to gain from disruption. Where a large company has no way for individual employees to initiate major changes in corporate strategy, a startup has fewer hops between employees and management. What's more, a startup that rewards an employee's good idea with a stock-grant ties that employee's future finances to the outcome of that idea – while a giant corporation's stock bonuses are only incidentally tied to the ideas of any individual worker.

Big companies are where good ideas go to die. If a big company passes on its employees' cool, disruptive ideas, that's the end of the story for that idea. But even if 100 VCs pass on a startup's cool idea and only one VC funds it, the startup still gets to pursue that idea. In startup land, a good idea gets lots of chances – in a big company, it only gets one.

Given how innately disruptable tech companies are, given how hard it is for big companies to innovate, and given how little innovation we've gotten from Big Tech, how is it that the tech giants haven't been disrupted?

The authors propose a four-step program for the would-be Tech Baron hoping to defend their turf from disruption.

First, gather information about startups that might develop disruptive technologies and steer them away from competing with you, by investing in them or partnering with them.

Second, cut off any would-be competitor's supply of resources they need to develop a disruptive product that challenges your own.

Third, convince the government to pass regulations that big, established companies can comply with but that are business-killing challenges for small competitors.

Finally, buy up any company that resists your steering, succeeds despite your resource war, and escapes the compliance moats of regulation that favors incumbents.

Then: kill those companies.

The authors proceed to show that all four tactics are in play today. Big Tech companies operate their own VC funds, which means they get a look at every promising company in the field, even if they don't want to invest in them. Big Tech companies are also awash in money and their "rival" VCs know it, and so financial VCs and Big Tech collude to fund potential disruptors and then sell them to Big Tech companies as "aqui-hires" that see the disruption neutralized.

On resources, the authors focus on data, and how companies like Facebook have explicit policies of only permitting companies they don't see as potential disruptors to access Facebook data. They reproduce internal Facebook strategy memos that divide potential platform users into "existing competitors, possible future competitors, [or] developers that we have alignment with on business models." These categories allow Facebook to decide which companies are capable of developing disruptive products and which ones aren't. For example, Amazon – which doesn't compete with Facebook – is allowed to access FB data to target shoppers. But Messageme, a startup, was cut off from Facebook as soon as management perceived them as a future rival. Ironically – but unsurprisingly – Facebook spins these policies as pro-privacy, not anti-competitive.

These data policies cast a long shadow. They don't just block existing companies from accessing the data they need to pursue disruptive offerings – they also "send a message" to would-be founders and investors, letting them know that if they try to disrupt a tech giant, they will have their market oxygen cut off before they can draw breath. The only way to build a product that challenges Facebook is as Facebook's partner, under Facebook's direction, with Facebook's veto.

Next, regulation. Starting in 2019, Facebook started publishing full-page newspaper ads calling for regulation. Someone ghost-wrote a Washington Post op-ed under Zuckerberg's byline, arguing the case for more tech regulation. Google, Apple, OpenAI other tech giants have all (selectively) lobbied in favor of many regulations. These rules covered a lot of ground, but they all share a characteristic: complying with them requires huge amounts of money �� money that giant tech companies can spare, but potential disruptors lack.

Finally, there's predatory acquisitions. Mark Zuckerberg, working without the benefit of a ghost writer (or in-house counsel to review his statements for actionable intent) has repeatedly confessed to buying companies like Instagram to ensure that they never grow to be competitors. As he told one colleague, "I remember your internal post about how Instagram was our threat and not Google+. You were basically right. The thing about startups though is you can often acquire them.”

All the tech giants are acquisition factories. Every successful Google product, almost without exception, is a product they bought from someone else. By contrast, Google's own internal products typically crash and burn, from G+ to Reader to Google Videos. Apple, meanwhile, buys 90 companies per year – Tim Apple brings home a new company for his shareholders more often than you bring home a bag of groceries for your family. All the Big Tech companies' AI offerings are acquisitions, and Apple has bought more AI companies than any of them.

Big Tech claims to be innovating, but it's really just operationalizing. Any company that threatens to disrupt a tech giant is bought, its products stripped of any really innovative features, and the residue is added to existing products as a "sustaining innovation" – a dot-release feature that has all the innovative disruption of rounding the corners on a new mobile phone.

The authors present three case-studies of tech companies using this four-point strategy to forestall disruption in AI, VR and self-driving cars. I'm not excited about any of these three categories, but it's clear that the tech giants are worried about them, and the authors make a devastating case for these disruptions being disrupted by Big Tech.

What do to about it? If we like (some) disruption, and if Big Tech is enshittifying at speed without facing dethroning-by-disruption, how do we get the dynamism and innovation that gave us the best of tech?

The authors make four suggestions.

First, revive the authorities under existing antitrust law to ban executives from Big Tech companies from serving on the boards of startups. More broadly, kill interlocking boards altogether. Remember, these powers already exist in the lawbooks, so accomplishing this goal means a change in enforcement priorities, not a new act of Congress or rulemaking. What's more, interlocking boards between competing companies are illegal per se, meaning there's no expensive, difficult fact-finding needed to demonstrate that two companies are breaking the law by sharing directors.

Next: create a nondiscrimination policy that requires the largest tech companies that share data with some unaffiliated companies to offer data on the same terms to other companies, except when they are direct competitors. They argue that this rule will keep tech giants from choking off disruptive technologies that make them obsolete (rather than competing with them).

On the subject of regulation and compliance moats, they have less concrete advice. They counsel lawmakers to greet tech giants' demands to be regulated with suspicion, to proceed with caution when they do regulate, and to shape regulation so that it doesn't limit market entry, by keeping in mind the disproportionate burdens regulations put on established giants and small new companies. This is all good advice, but it's more a set of principles than any kind of specific practice, test or procedure.

Finally, they call for increased scrutiny of mergers, including mergers between very large companies and small startups. They argue that existing law (Sec 2 of the Sherman Act and Sec 7 of the Clayton Act) both empower enforcers to block these acquisitions. They admit that the case-law on this is poor, but that just means that enforcers need to start making new case-law.

I like all of these suggestions! We're certainly enjoying a more activist set of regulators, who are more interested in Big Tech, than we've seen in generations.

But they are grossly under-resourced even without giving them additional duties. As Matt Stoller points out, "the DOJ's Antitrust Division has fewer people enforcing anti-monopoly laws in a $24 trillion economy than the Smithsonian Museum has security guards."

https://www.thebignewsletter.com/p/congressional-republicans-to-defund

What's more, Republicans are trying to slash their budgets even further. The American conservative movement has finally located a police force they're eager to defund: the corporate police who defend us all from predatory monopolies.

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

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