Breaking: CFTC Chair Reiterates "ETH Is Commodity" Stance Amid SEC Lawsuits

CoingapePubblicato 2023-06-07Pubblicato ultima volta 2023-06-07

Introduzione

Speaking in a US House Committee hearing on “The Future of Digital Assets: Providing Clarity for Digital Asset Spot Markets,” Behnam reiterated his stance on Ethereum being a commodity.

Crypto Market News: US Commodity Futures Trading Commission (CFTC) Chairman Rostin Behnam on Tuesday reiterated his stance that Ethereum is a commodity and not security. This comes at a time when the U.S. Securities and Exchange Commission (SEC) filed back to back complaints against two of the world’s top crypto exchanges, Binance and Coinbase over violation of financial regulations. The SEC had been emphasizing that crypto businesses operating in the United States come forward and register digital asset trade related operations with it. However, there is no clarity as to which laws would the crypto assets fit under.

Gary Gensler, the SEC Chair had recently stirred a controversy in the crypto market by saying that everything other than Bitcoin is a security. He maintains that Bitcoin is not a security but a commodity under the CFTC’s jurisdiction. On the contrary, CFTC Chair Behnam had been saying that Ethereum qualifies as a commodity. This confusion and uncertainty, as things stand, is still not resolved although efforts are on with a draft bill to categorize which assets are securities and commodities.
“Ethereum Is A Commodity”

Speaking in a US House Committee hearing on “The Future of Digital Assets: Providing Clarity for Digital Asset Spot Markets,” Behnam reiterated his stance on Ethereum being a commodity. The question arose when Congressman Austin Scott said crypto assets were clearly not securities and that the assets should be regulated by the CFTC and not the SEC. The CFTC Chair replied,
“I’ve argued in the past that Ether is a commodity.”

Letture associate

Jensen Huang: Prompts are Becoming Obsolete, Loops are the New Paradigm

Jensen Huang, alongside AI leaders like Peter Norvig, Boris Cherny, and Andrew Ng, is advocating for a shift from "prompt engineering" to "loop engineering" as the new paradigm for AI development. Instead of manually crafting individual prompts, the focus is now on designing autonomous loops—systems where AI agents execute tasks, self-validate results, and iterate until completion without constant human oversight. A loop is a management framework that enables agents to operate independently. Key implementations are seen in Claude Code (with features like /loop, /goal, and /schedule) and OpenAI Codex, which employ multiple agents working in parallel within isolated environments. A core principle is the separation of roles: one agent (or model) performs the task, while an independent agent (or a smaller, separate model) validates the output to ensure objectivity. The article outlines a practical roadmap for implementing loops, starting with a "four-condition test" to assess suitability, building a minimal viable loop, and emphasizing critical pitfalls to avoid, such as lacking hard stop conditions or allowing loops to handle tasks requiring human judgment. This evolution is framed as the fourth major shift in AI interaction: from Prompt Engineering (crafting instructions) to Context Engineering (providing background information), then to Harness Engineering (building tool-enabled environments), and finally to Loop Engineering (creating self-sustaining systems). This progression reflects a consistent trend of increasing abstraction, moving human involvement from direct instruction to system design and rule-setting. The concept has academic roots in frameworks like ReAct, which formalized the "reason-act-observe" cycle. While loop engineering promises greater automation, experts caution about managing token costs and warn against outsourcing understanding—AI can assist, but deep problem comprehension remains essential.

marsbit55 min fa

Jensen Huang: Prompts are Becoming Obsolete, Loops are the New Paradigm

marsbit55 min fa

MemeCore Token Crashes As ZachXBT Warning Puts Insider Supply Back In Focus

MemeCore's M token experienced a severe crash, plunging over 70% in a single session. This sudden sell-off revived concerns highlighted by on-chain investigator ZachXBT regarding tokens with concentrated insider supply and thin liquidity. The incident underscores the fragility of many memecoins, where large paper valuations can vanish quickly when selling pressure hits illiquid markets. It also brings exchange listing standards into question, as listings can imply a legitimacy not supported by the underlying token structure. The crash serves as a stark warning for traders that social traction and high market capitalization do not guarantee resilient liquidity, emphasizing the risks inherent in high-beta crypto assets.

bitcoinist1 h fa

MemeCore Token Crashes As ZachXBT Warning Puts Insider Supply Back In Focus

bitcoinist1 h fa

GPT Designs GPT

OpenAI has unveiled its first custom AI chip, Jalapeño, a move signaling a strategic shift beyond being a mere model company. While many see it as a challenge to NVIDIA, its core aim is to control the entire intelligent production pipeline—from models and chips to data centers and energy. The key driver is the evolving competitive landscape: model advantages are shrinking, while the computational gap in areas like cost-per-token, system throughput, and energy efficiency is becoming the true long-term barrier. Jalapeño is primarily an inference chip, targeting the massive and growing "inference tax"—the daily operational cost of generating tokens for services like ChatGPT and APIs. By designing its own hardware optimized for its specific workloads and future product roadmaps (even using AI to aid the chip design process), OpenAI aims to drastically reduce token generation costs and improve system efficiency. This creates a potential flywheel: better models help design better chips, which lower costs for running next-generation models, supporting more users and products, which in turn provides more data to refine future chips. The strategy mirrors Apple’s integrated approach, building a closed loop where hardware, software, and applications are co-optimized. In the long term, OpenAI is not trying to become the next NVIDIA (a supplier of "shovels" to all AI companies) but to own and operate the entire "mine"—selling the end product of intelligence itself. This move marks OpenAI's ambition to evolve from creating the smartest models to controlling the foundational infrastructure of AI production.

marsbit1 h fa

marsbit1 h fa

Ethereum Foundation Interim Executive Director Speaks Out: What Is Our Mission?

The Ethereum Foundation's core mission is to ensure Ethereum remains a truly permissionless, censorship-resistant, private, and open infrastructure for large-scale, sovereign coordination. The article clarifies the EF's focus and dismisses irrelevant objectives, such as pursuing institutional popularity or short-term speculation. Its core work centers on eliminating systemic weaknesses. This involves fortifying Ethereum across multiple layers—protocol, access, user, and institutional—against exploitation, control, or surveillance. Key initiatives include minimizing harmful MEV and preventing privileged control over transaction flow, making unconditional privacy a foundational default, ensuring staking remains permissionless and decentralized, and strengthening user-facing access points to uphold autonomy. Concurrently, the EF aims to seize strategic opportunities. These include leading the transition to post-quantum cryptography, achieving a fully verifiable protocol stack, establishing Ethereum as private digital cash, integrating user-owned AI agents with personal wallets, and demonstrating that trusted-neutral infrastructure can competitively handle disintermediated coordination at an institutional scale. The article also addresses recent organizational changes, stating that personnel departures were due to strategic realignment, role fit, or natural evolution. It clarifies the approach to spin-outs, emphasizing that external funding will be provided only for work critical to the EF's mission that reduces Ethereum's dependency without creating new risks or mission drift. Ultimately, the EF is committed to building an enduring, neutral system that reshapes global coordination, focusing relentlessly on the principles of censorship resistance, openness, privacy, and sovereignty (CROP).

链捕手2 h fa

Ethereum Foundation Interim Executive Director Speaks Out: What Is Our Mission?

链捕手2 h fa

Switching Research Fields in the Final Year of My PhD, I Landed an Offer from OpenAI: My Interview Journey Was Full of 'Surprises'

Yong Zheng-Xin, a final-year PhD student at Brown University, secured an OpenAI offer after pivoting from multilingual models to AI safety research in his last year. In his blog post "Surprising lessons from my research scientist job search," he shares six unexpected insights from his job hunt. He found that often only one or two key papers matter for securing an interview, not the total number. Interview formats were highly diverse, including unexpected rounds on system design and AI agent usage. "Work trials," common in AI startups, involved paid, sometimes week-long collaborative tasks that disrupted other interview preparations. Timing proved crucial, with opportunity windows sometimes lasting less than a month. Return offers for research roles were rare compared to software engineering. Surprisingly, many interview rounds were unrelated to his specific AI safety focus, instead testing broader research competencies. Zheng-Xin concludes that the ability to demonstrate relevant expertise in a new field can unlock opportunities, regardless of one's previous publication record.

marsbit2 h fa

Switching Research Fields in the Final Year of My PhD, I Landed an Offer from OpenAI: My Interview Journey Was Full of 'Surprises'

marsbit2 h fa

Trading

Spot

Futures