Kevin Rose’s Straightforward Test for AI Hardware: Would You Want to Punch Someone Wearing It?

Kevin Rose’s Unique Take on AI Hardware Investments

Kevin Rose believes in a visceral rule for evaluating AI hardware: “If you want to punch someone in the face for wearing it, you probably shouldn’t invest in it.”

A Candid Perspective from a Seasoned Investor

This bold assessment comes from Kevin Rose, a general partner at True Ventures and an early investor in notable brands like Peloton, Ring, and Fitbit. While many venture capitalists rush to back the latest trend in smart wearables, Rose is taking a more cautious approach amid the AI hardware gold rush in Silicon Valley.

The Challenges of AI Wearables

“Let’s listen to the entire conversation,” Rose states, critiquing current AI wearable technology for breaching social constructs around privacy. His experience on the board of Oura, which holds 80% of the smart ring market, reveals the fine line between technical capabilities and emotional resonance. Successful wearables thrive on social acceptability.

Emotional Impact Drives Investment Decisions

Rose emphasizes the emotional landscape of technology: “As an investor, you have to consider how technology makes you feel and how it impacts those around you.” He views the persistent “always-on” nature of AI as detrimental to human interactions.

A Personal Encounter with AI Wearables

Rose recounts his experience with AI wearables, including the ill-fated Humane AI pendant. A memorable moment came when he attempted to use the wearable to settle an argument with his wife. “That was the last time I wore that thing,” he laughs, highlighting the personal tensions that technology can create.

A Critical View on AI-Enhanced Experiences

Rose critiques trivial AI use cases, like asking smart glasses about monuments. “We bolt AI onto everything, and it’s ruining the world,” he argues, reflecting on the implications of modifying photos and altering perceptions of reality.

Lessons from Early Social Media

He draws parallels between the present AI landscape and the early days of social media, warning that seemingly harmless decisions may have lasting repercussions. “We’ll look back and think, ‘Was it a good idea to slap AI on everything?’”

Navigating AI’s Complex Challenges with Children

As a father, Rose faces his own challenges explaining AI to his children. After using OpenAI’s Sora to generate adorable puppy videos, he found himself explaining that these were not real pets. His solution? Compare the AI to movie magic to make it relatable.

Optimism for the Future of AI and Entrepreneurship

Despite his critiques, Rose is enthusiastic about AI’s transformative potential for entrepreneurship and venture capitalism. “Barriers to entry are shrinking daily,” he notes, recounting colleagues who have successfully built apps using AI coding tools.

Shifting Dynamics in Venture Capital

These advancements could reshape the VC ecosystem, allowing entrepreneurs to delay funding or operate without it entirely. “This will greatly change the world of VC, and I think for the better,” Rose predicts.

Reassessing the Role of Venture Capitalists

While some venture firms hire numerous engineers, Rose believes the real value lies in emotional intelligence. “The challenges entrepreneurs face are often emotional,” he asserts, underscoring the need for VCs who can offer long-term support.

What Rose Looks for in Founders

Rose recalls advice from Larry Page, urging the importance of seeking founders who disregard the impossible. “We want bold ideas that challenge the norms,” he concludes. “Even if they fail, we appreciate their mindset and will back them again.”

Here are five FAQs inspired by Kevin Rose’s simple test for AI hardware:

1. Q: What is Kevin Rose’s "punch in the face" test for AI hardware?

A: Kevin Rose’s test is a humorous way to evaluate the acceptability of AI hardware. It asks: "Would you want to punch someone in the face who’s wearing it?" If the answer is yes, the hardware likely has aesthetic or usability issues that might deter users.

2. Q: Why is this test relevant for evaluating new AI gadgets?

A: The test helps assess the social and emotional reactions people have to technology. If the design is off-putting or intrusive, it might indicate a failure in user experience, which is crucial for the adoption of technology.

3. Q: Can the "punch in the face" test apply to software as well?

A: While it is primarily aimed at hardware, the underlying idea can extend to software. If a user feels frustrated or angry while using an app, it may signal poor usability or design.

4. Q: How can developers use this test to improve their products?

A: Developers can gather feedback during the design phase, asking potential users if the product evokes any negative feelings. This can lead to iterative improvements that enhance the overall experience.

5. Q: Are there examples of AI hardware that fail this test?

A: Yes, some early wearable devices or bulky VR headsets faced criticism for their awkward design, making many users uncomfortable. Dissatisfaction often led to a desire for more user-friendly, aesthetically pleasing options.

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Soaring Energy Costs Target AI and Data Centers

Consumers Fear Rising Electricity Costs Amid Data Center Expansion

As tech companies announce ambitious plans for new data centers, a recent survey reveals mounting consumer concern that this AI-driven growth may lead to increased electricity prices.

Survey Insights: Consumer Worries Intensify

A report commissioned by Sunrun, a solar energy installer, shows that 80% of consumers are anxious about how data centers may impact their utility bills.

Electricity Demand Trends: A Shift in Usage

These concerns are grounded in reality. According to the U.S. Energy Information Administration (EIA), electricity demand in the United States remained stable for over a decade. However, in the last five years, commercial users, notably data centers, have significantly increased their consumption, with annual growth rates of 2.6% and 2.1% for data centers and industrial users, respectively. In contrast, residential use has only seen a modest increase of 0.7% annually.

Data Centers’ Growing Energy Footprint

Currently, data centers account for approximately 4% of the electricity generated in the U.S., a figure that has more than doubled since 2018. Projections indicate that this could rise to between 6.7% and 12% by 2028, as reported by Lawrence Berkeley National Laboratory .

Renewable Energy Solutions: A Double-Edged Sword

While the electricity generation industry is meeting rising demand through new solar, wind, and battery storage technologies, there is cautious optimism. Major tech companies are securing large contracts for utility-scale solar projects, attracted by the energy source’s affordability and modularity. Solar farms are capable of providing power to data centers even before full completion, typically taking around 18 months to finish.

Political Influence on Renewable Growth

The EIA anticipates that renewables will dominate new generating capacity for at least the coming year. However, experts warn that changes in political leadership could hinder this growth, particularly if key aspects of the Inflation Reduction Act are repealed.

Natural Gas Supply Challenges

Natural gas, another favored energy source for data center operations, is struggling to keep pace. While production has increased, much of it is directed toward exports rather than domestic supply. From 2019 to 2024, electricity generators’ consumption rose by 20%, while exports jumped by an astonishing 140%.

Prolonged Construction Times for New Power Plants

The construction timelines for new natural gas power plants compound the issue, as they take about four years to complete, per the International Energy Agency. A backlog in turbine production for gas-fired plants further complicates the situation, with delivery schedules extending up to seven years, according to industry reports .

The Backlash Against AI and Data Centers

While AI and data centers aren’t solely to blame for the surge in electricity demand—industrial users have been significant contributors—they remain the focal point of public concern. A recent Pew survey revealed that consumers are more worried than excited about AI, especially as businesses increasingly leverage the technology to downsize rather than to enhance productivity.

Final Thoughts: The Rising Energy Prices Dilemma

With energy prices on the rise, it’s clear a backlash may be brewing against the rapid expansion of data centers fueled by AI technology.

Here are five frequently asked questions (FAQs) regarding the impact of rising energy prices on AI and data centers:

FAQ 1: Why are rising energy prices a concern for AI and data centers?

Answer: Rising energy prices increase operational costs for AI and data centers, which are already energy-intensive due to their high computational demands. This affects profitability, operational scalability, and resource allocation, potentially slowing down advancements in AI technology.

FAQ 2: How do energy costs impact AI development?

Answer: As energy costs rise, the cost of training AI models, especially large-scale ones, also increases. Organizations may have to limit the number of experiments or reduce the size of datasets used for training, which can hinder innovation and the pace of AI advancements.

FAQ 3: What measures can data centers take to mitigate rising energy costs?

Answer: Data centers can implement energy-efficient technologies, optimize cooling systems, invest in renewable energy sources, and deploy AI-driven management systems to monitor and reduce energy consumption, ultimately minimizing costs.

FAQ 4: Are there any benefits to rising energy prices for the AI industry?

Answer: Yes, rising energy prices can spur innovation in energy-efficient computing and incentivize the development of sustainable technologies. This could lead to breakthroughs in low-power AI solutions and encourage investment in greener data center practices.

FAQ 5: How are organizations responding to energy price fluctuations in AI operations?

Answer: Organizations are increasingly prioritizing energy efficiency as a key factor in their IT strategies. Many are exploring partnerships with renewable energy providers, optimizing their infrastructure, and adopting AI to improve energy use in real-time, balancing performance with cost management.

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AI Frenzy Derails CoreWeave’s Acquisition of Core Scientific — Now Acquiring Python Notebook Marimo

Core Scientific Shareholders Reject $9 Billion Acquisition by CoreWeave

Core Scientific shareholders on Thursday voted against a $9 billion all-stock acquisition offer from partner and competitor CoreWeave.

Major Shareholder Influence in Voting Decision

The decision came after a recommendation from the largest shareholder, Sina Toussi of Two Seas Capital, a firm specializing in post-bankruptcy companies. Core Scientific emerged from bankruptcy in January 2024.

Shared Origins: From Crypto Mining to AI

Core Scientific started as a cryptocurrency mining company, a path it also shares with AI data center provider CoreWeave. The latter has evolved to focus on AI workloads, aided by its partnership with investor Nvidia. Since its IPO, CoreWeave’s market cap has skyrocketed from $14 billion to $66 billion (approximately $140 per share), attracting investor interest in AI advancements.

CoreWeave’s Contract and Acquisition Strategies

CoreWeave previously signed a $10 billion, 12-year contract with Core Scientific to leverage its facilities for AI services and had also announced plans to acquire the company outright, offering a premium over Core Scientific’s stock price.

Strategic Outlook from Investors

However, investor Toussi believes Core Scientific has the potential to independently thrive in the AI sector. In his opposition letter, he stated, “Since the transaction was announced in July, investment in AI infrastructure has accelerated, driving equity valuations of Core Scientific’s peers to new heights. Why would anyone vote for a transaction worth only $16.40 per share?”

Market Reaction and Future Prospects

Following the rejection of the deal, Core Scientific’s stock experienced an uptick, reflecting a current market cap of $6.6 billion.

AI Bubble Signs?: Investor Behavior in Acquisition Landscape

The recent trend of investors rejecting acquisition offers in hopes of more lucrative deals indicates the possibility of an impending AI bubble.

CoreWeave Expands Its Portfolio

In the meantime, CoreWeave continues to pursue acquisitions, recently acquiring Marimo, an open-source competitor to Jupyter Notebook, for an undisclosed amount. PitchBook estimates that Marimo has raised around $5 million.

The Role of Python Notebooks in AI Development

Python notebooks, which combine code, rich media, and explanatory text into single shareable files, are essential for interactive data analysis and AI app development. This acquisition helps CoreWeave advance from simple hosting services to developing AI applications.

Sure! Here are five FAQs addressing the acquisition of Marimo, a Python notebook platform, by CoreWeave’s Core Scientific:

FAQ 1: What is Marimo?

Answer: Marimo is a Python notebook platform designed for data analysis and machine learning. It allows users to write and execute Python code in a collaborative, interactive environment, making it easier to explore datasets and visualize results.

FAQ 2: Why did CoreWeave acquire Marimo?

Answer: CoreWeave acquired Marimo to enhance its data science and machine learning capabilities. By integrating Marimo’s user-friendly notebook environment, CoreWeave aims to provide its clients with more powerful tools for data analysis and innovation, streamlining workflows for data scientists and analysts.

FAQ 3: How will this acquisition impact existing Marimo users?

Answer: Existing Marimo users can expect continued support and enhancements to the platform. CoreWeave plans to integrate additional features and infrastructure improvements, providing a smoother experience, while maintaining the core functionalities that users appreciate.

FAQ 4: What benefits does this acquisition offer to CoreWeave customers?

Answer: CoreWeave customers will gain access to advanced data science tools and a collaborative platform for coding and analysis. The integration of Marimo’s capabilities allows users to leverage cutting-edge machine learning resources directly within their existing workflows, increasing efficiency and innovation.

FAQ 5: Will Marimo remain an independent platform after the acquisition?

Answer: While Marimo will be integrated into CoreWeave’s offerings, it is expected to operate under its own brand. CoreWeave aims to preserve the unique features of Marimo while enhancing its functionalities and user experience in alignment with CoreWeave’s broader business goals.

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