Jev, and state of AI tools

 The rise and fall of Jev - Alex Ewerlöf Notes

The article, titled "The rise and fall of Jev," uses the rapid hype cycle and quick disillusionment surrounding a new AI model called Jev as a case study to examine the current state of the AI industry. The author explores how marketing hype and tech buzzwords override critical thinking, contrasts this with four years of genuine incremental progress since ChatGPT launched, and outlines the fundamental problems that AI still has not solved.

• The Anatomy of the Jev Hype: Jev was marketed as a revolutionary "System One Model"—a fast, general-purpose classification model trained via a new method called Reinforcement Learning for Calibrated Decisions (RLCD).
  
  
• The Hype Claims: It was hyped with high-profile name-dropping, claims of being exponentially cheaper, and assertions that it "cannot hallucinate."
  
  
• The Reality Check: The hype quickly collapsed into the "Trough of Disillusionment" when users realized that while Jev outputs valid schemas (hence "no hallucination"), it can still be entirely wrong, and other open-weight models match its cost-to-performance ratio.
  
  
• Four Years of Incremental Improvements: Progress since GPT-2 and ChatGPT has been steady and practical rather than magical, introducing instruction-tuned models, function calling, coding harnesses, AI agents, larger context windows, multimodal capabilities, and Model Context Protocol (MCP).
  
  
• Why the AI Hype Persists: The industry is driven forward by fierce US-China geopolitics, a massive interdependent financial debt bubble that has to succeed, constant fear narratives around "rogue AI," and the direct disruption of white-collar and software engineering jobs.
  
  
• What AI is Still Missing: Neural networks still lack true abstract reasoning (System 2 logic), continuous real-time learning, the rapid sensory and motor precision required for embodied robotics, and the ultra-low energy efficiency of the human brain.
  
  
• Takeaways on Tech Marketing: The author advises readers to look past name-dropping, confusing jargon, ambiguity, and manufactured drama, noting that big claims require substantial, unbiased evidence.

Jev is Vercel's fastest-adopted AI model ever | TechCrunch

• Record-Breaking Adoption: Data from Vercel reveals that a decision-making AI model named Jev (created by TypeSafe AI) became its fastest-adopted AI model ever. Within two weeks of its mid-September release, it was actively used by 35% of paid teams—nearly double the reach of the second most popular model, Sonnet 5.5.
  
  
• Why Jev is Popular: Jev is a lightweight model designed specifically to choose between a few predetermined outputs rather than generating long free-form text. This makes it significantly cheaper and faster to run than standard models, making it ideal for high-volume data classification tasks (such as Vercel using it to classify harmful commands).
  
  
• Market Impact: Jev's success has inspired competing rapid-classification offerings from tech giants like OpenAI and Amazon.
  
  
• Broader Trends: Vercel's AI gateway data also highlights strong momentum for open-source models (accounting for over 70% of processed tokens), alongside rapid tenfold growth in spending on proprietary frontier labs.

Introducing System One Models & Jev - TypeSafe AI Blog

Levittown housing story; AI video?

Interesting story and video.
But, is this video AI generated, and how historically accurate it is?
Here is Wikipedia info:

There are three major planned communities known as Levittowns built by Levitt & Sons in New York, Pennsylvania, and New Jersey. [1, 2]

Levittown, New York (Nassau County)

Location: Long Island, about halfway between Hempstead and Farmingdale.
History: It was the first Levittown, built between 1947 and 1951.
Type: Unincorporated community and census-designated place (CDP).
Population: Around 51,758 people.
Read more: Levittown, New York - Wikipedia [1, 2, 3]

Levittown, Pennsylvania (Bucks County)

Location: Lower Bucks County, part of the Philadelphia metropolitan area.
History: It was the second Levittown, built during the 1950s as a massive planned suburban development.
Type: Census-designated place (CDP) spanning multiple municipalities.
Population: Around 52,699 people.
Read more: Levittown, Pennsylvania - Wikipedia [1, 2, 3, 4, 5, 6]

Willingboro Township, New Jersey (Burlington County)

Location: South Jersey, near Trenton and Philadelphia.
History: Originally and commonly known as Levittown, New Jersey, it was built by William Levitt in 1955 as the third and largest Levittown project. It was later renamed Willingboro Township.
Type: Official township in Burlington County.
Read more: Willingboro Township, New Jersey - Wikipedia [1, 2, 3]

Why America Can't Save Its Own Dream - YouTube by Paul McAllister

The video, titled "Why America Can't Save Its Own Dream" by creator Paul McAllister, examines the history and downfall of the post-WWII American suburban ideal through the lens of Levittown, Long Island. It traces how government subsidies, mass-production homebuilding, and institutionalized racial segregation created an unsustainable model of homeownership that laid the groundwork for today's housing crisis.

Key Takeaways

• Mass-Produced Suburbs: In 1949, Levitt & Sons used assembly-line techniques on Long Island potato fields to build cheap, standardized homes ($7,990), selling over 1,400 contracts in a single day to returning WWII veterans.
  
  
• State-Subsidized Prosperity: The rapid expansion was enabled by government backing—specifically FHA and VA loans—allowing working-class families to secure housing with minimal down payments.
  
  
• Institutionalized Segregation: FHA guidelines (such as the 1938 Underwriting Manual) and racially restrictive covenants systematically excluded Black families from purchasing these homes to maintain high neighborhood property ratings.
  
  
• Civil Rights & Resistance: Despite the 1948 Supreme Court ruling (Shelley v. Kraemer) deeming restrictive covenants legally unenforceable, developers like Levitt continued racial exclusion through private contracts, prompting civil rights struggles (such as the 1957 integration of Levittown, PA by William and Daisy Myers).
  
  
• Current Affordability Crisis: The model created an illusion of cheap, endless expansion that ultimately transformed modern suburban real estate into an inaccessible, high-cost market ($700k+ median prices in former boomtowns) driven by NIMBYism, zoning restrictions, and rising infrastructure costs.
  
  

---

Historical Accuracy Assessment

The historical claims made in the video are highly accurate and align with established historical scholarship:

• FHA Guidelines & Redlining: The 1938 FHA Underwriting Manual explicitly used racial composition as a primary risk factor when valuing neighborhoods, effectively codifying redlining and residential segregation across suburban developments.
  
  
• Shelley v. Kraemer (1948): The Supreme Court indeed ruled that state courts could not enforce racially restrictive covenants, though developers used private loopholes for years afterward.
  
  
• The Myers Family (1957): William and Daisy Myers were the first Black family to move into Levittown, Pennsylvania, where they faced intense community hostility, police indifference, and mob intimidation—a well-documented event in civil rights history.
  
  

---

Use of AI Tools

While the underlying research and narrative structure stem from real historical records, the production likely relies heavily on AI assistance:

• AI-Assisted Narration / Voice Synthesis: The narrator's voice has a synthetic, uniform cadence and polished rhythm characteristic of modern text-to-speech (TTS) voice models or heavily post-processed voice clones.
  
  
• Scripting & Visual Assembly: The high-frequency upload schedule of long-form documentaries on this channel suggests the use of AI-assisted research summaries and automated workflow scripts to organize archival footage and public records efficiently.