cross-posted from: https://lemmy.world/post/47499598

We’ll soon get a chance to see whether, frankly, our last hope, evil corp Google, can still distinguish content created by AI from Human one 🤖

Here’s how I would rank the detection difficulty: 1️⃣ Text 2️⃣ Code 3️⃣ Images 4️⃣ Gifs 5️⃣ Videos If they already fail at level 5, we have a SERIOUS problem.

alternative video upload: https://streamable.com/e/r2uuco

cross-posted from: https://hexbear.net/post/8624879

https://www.axios.com/2026/05/28/ai-spending-roi-enterprise-costs

Archive link https://web.archive.org/web/20260528114303/https://www.axios.com/2026/05/28/ai-spending-roi-enterprise-costs

Why it matters: Companies that rushed to embrace AI are now confronting ballooning IT costs, uncertain productivity gains and growing employee skepticism.

Driving the news: Microsoft canceled most of its Claude Code licenses, in part over costs, according to The Verge, and Uber's COO said AI costs are getting "harder to justify."

An AI consultant tells Axios one of their clients recently spent half a billion dollars in a single month after failing to put usage limits on Claude licenses for employees.

Companies are citing AI's ability to automate jobs as a cause for layoffs, though Anuj Kapur, CEO of CloudBees, told Axios that workforce cuts may simply be "the only lever they can pull" to offset their AI bills.

Consumer sentiment around AI is also nosediving, and employees are rebelling against the use of the technology at work. 

What they're saying: The enterprise is undergoing a "healthy swing" away from AI overuse — or "tokenmaxxing," the push to burn as many AI tokens as possible — Ali Ansari, CEO of model training firm Micro1, told Axios.

Ansari hopes this correction will push companies toward more efficient AI use.
While the market views these tools as working equally well across the enterprise, Ansari says "the reality of AI right now is that it only works for coding."
That disconnect can drive up IT bills without leading to high return on investment in agents, he said. 

Friction point: Corporate AI adoption is running into four unique problems.

Use cases: "Most people default to automating tasks they dislike rather than tasks most valuable to the company," Sophia Velastegui, CEO of Velastegui Ventures and former chief AI officer at Microsoft told Axios. Instead, they should focus on using AI to drive revenue.

Costs: One CTO told Axios that employees were using AI models to check the weather. That gets expensive fast: Enterprise AI plans are not truly 'all you can eat,' and even simple chatbot queries can carry heavy token costs.

There is no alternative to terrestrial silicon based chips. GaN over SiC can only make an overclocked pentium 1 (1993) chip. Even when using liquid oil mist cooling to prevent massive radiative cooling black panels, $55m total lauch costs for 3 NVL72 systems results in a 5 year payback period GPU rental rate of $6.66/hr. Over 50% higher than terrestrial rates, with bad latency.

The entire proposition was BS from the start to justify rocket company merger with AI failure. But is now IPO BS to pretend SpaceX IPO is not garbage.

An un-amortized 10% target cannot be sustained over 20 years if the data center's initial rates are forced down to match terrestrial market pricing [finance]. Forcing a strict 50% revenue drop every 5 years from these competitive baselines dramatically impacts the un-amortized annual Return on Investment (ROI) for the $55.5 million installation.The financial performance updates for both the optimistic and pessimistic scenarios highlight the impact of these changes

1. The Optimistic Scenario (Capped at $4.08/Hour Peak)

This layout assumes the space capsule launches at the top of the 2026 Ornn Index price spectrum ($4.08/hr), but fails to capture a premium from sovereign or defense clients. Over its 20-year lifespan, the 216-GPU cluster generates $71,700,445 in total lifetime revenue.The declining un-amortized ROI and hourly rates are structured as follows:

• Years 1 to 5: $4.08 / hour ──► Annual Revenue: $7.65M ──► Annual ROI: 13.78%Years
• 6 to 10: $2.04 / hour ──► Annual Revenue: $3.82M ──► Annual ROI: 6.89%
• Years 11 to 15: $1.02 / hour ──► Annual Revenue: $1.91M ──► Annual ROI: 3.45%
• Years 16 to 20: $0.51 / hour ──► Annual Revenue: $0.96M ──► Annual ROI: 1.72%

The Optimistic Financial Verdict

20-Year Average Annual ROI: 6.46%

The Problem: The data center technically pays for itself, netting $16.2 million over its initial CapEx. However, a 6.46% average un-amortized return fails to compete with basic terrestrial indexes. For an infrastructure project carrying intense orbital launch risk, a venture capital firm would immediately reject these metrics.

2. The Pessimistic Scenario (Constrained to $2.75/Hour Floor)

This layout assumes hyper-aggressive terrestrial spot platforms like Nebius or similar cloud under-cutters force the space data center down to the absolute bottom of the market floor ($2.75/hr) from Day 1. Over its 20-year lifespan, the capsule brings in only $48,327,506 in total lifetime revenue.The collapsing financial yield is structured as follows:

• Years 1 to 5: $2.75 / hour ──► Annual Revenue: $5.15M ──► Annual ROI: 9.29%
• Years 6 to 10: $1.38 / hour ──► Annual Revenue: $2.58M ──► Annual ROI: 4.64%
• Years 11 to 15: $0.69 / hour ──► Annual Revenue: $1.29M ──► Annual ROI: 2.32%
• Years 16 to 20: $0.34 / hour ──► Annual Revenue: $0.64M ──► Annual ROI: 1.16%

The Pessimistic Financial Verdict 20-Year Average Annual ROI: 4.35%

The Problem: This scenario represents financial bankruptcy. The entire 20-year lifetime revenue ($48.3M) falls short of the initial $55.5M build and launch cost. The system loses a raw $7.17 million over its lifespan, proving that matching terrestrial commodity price floors destroys the commercial viability of a space-based data center.

3. How a 20-Year-Old Chip Distorts the Value Floor

To understand why the final blocks ($0.51/hr and $0.34/hr) fail commercially, we look at what happens when you attempt to rent a 20-year-old chip.If you tried to sell time on a 2006 GeForce 8800 GTX (345 GFLOPS) today, you could not find a customer at any price point. A modern, cheap microcontroller found inside a common appliance processes telemetry faster and with less power.

By Year 15 to 20, the space data center's 45-TFLOPS Blackwell chips are drastically outmatched by newer ground architectures. Even if you cut your price to 34 cents an hour, your compute-value per dollar is thousands of times worse than renting a sliver of a 2046 terrestrial chip.

Final Business Analysis

If forced to compete head-to-head on pricing with Earth-bound data centers, the orbital data center is dead on arrival. The project only makes sense if you treat the $55.5 million CapEx as a non-commercial, sunk-cost defense asset—an un-hackable, un-cooled sovereign vault where the goal is data permanence, physical survivability, and continuous processing through a planetary crisis, entirely detached from standard market economics.

We are in a golden era for buying and selling digital LPs. While I’ll use Bandcamp, sleek alternatives like Ampwall, Subvert, and Mirlo are equally great options. These online markets inherently incentivize artists to avoid filler or risk losing a sale, while the subscription streaming model requires artists to pad their catalog for pay per play. Streaming has revived the worst trope of the old music industry: the album that is just "two hits and a bunch of crap."

Spotify’s business model demands album filler because the platform pays out royalties based on "stream share" which trigger a payout the second a track hits the 30 second mark, incentivizing artists to maximize volume over value. This has fundamentally warped modern songwriting: albums are aggressively padded with short, two minute tracks and repetitive hooks designed specifically to feed the algorithm and inflate stream counts. On Spotify, a deep, cohesive artistic statement takes a back seat to sheer data output, turning what should be a focused LP into a bloated playlist of algorithmic bait.

Accidental hits happen way more often than you’d think. As it turns out, artists are notoriously bad at predicting their own success. When you buy a digital LP on a platform like Bandcamp, you are investing in a complete and curated piece of art where even the tracks the artist never expected to blow up exist naturally as part of a cohesive story. On subscription services like Spotify, those same happy accidents are treated like lottery tickets while surrounded by cynical, algorithm optimized filler designed just to farm streams. Buying the album ensures you are experiencing those unexpected gems as genuine creative discoveries, rather than digging through algorithmic bloat to find them.

Bandcamp serves the genre; streaming serves the algorithm. When producers target platforms like Spotify, artistic nuances like tempo variations and volume dynamics are sacrificed to strict LUFS loudness standards and predictable, club friendly danceability. This algorithmic pressure strips electronic and club music of its experimental edge, forcing tracks into a uniform, compressed sonic mold just to survive on a playlist. On Bandcamp, however, the music is freed from these rigid streaming constraints, allowing producers to prioritize raw genre authenticity and dynamic storytelling over sanitized, playlist ready optimization. Soundtrack and orchestral music have become major casualties of this shift, as their essential cinematic highs and quiet, emotional lows are flattened into a lifeless wall of sound just to meet streaming's volume requirements.

Just so we're clear, I'm not here to sell you my album. Go ahead and enjoy the whole thing ad free on my website. https://thejoyo.com/#more