Terra Classic Continues To Brush Off Market Downtrends, Buy Now?

newsbtcPublicado em 2023-06-14Última atualização em 2023-06-14

Resumo

The crypto market has been bleeding lately, and leaders like Bitcoin and Ethereum have been on a downtrend. In addition, the Securities and Exchange Commission's crackdown on top trading platforms...

The crypto market has been bleeding lately, and leaders like Bitcoin and Ethereum have been on a downtrend. In addition, the Securities and Exchange Commission’s crackdown on top trading platforms Coinbase and Binance has further made things worse as the crypto winter has persisted. 
However, while the massacre caught up with most coins, Terra Classic (LUNC) remained in the uptrend, emerging as the number 1 gaining cryptocurrency over the past 24 hours.
Terra Classic (LUNC) Making Bold Rebound Moves
LUNC surprised market participants over the past week as it continued pulling weight amid bearish trends in the crypto market. Before the disaster enveloped the Terra ecosystem in May 2022, Terra Classic (LUNC) traded at an all-time high of $116. 
LUNC’s value plummeted following the crash of Terra blockchain’s stablecoin UST, wiping over $40 billion valuation for the token’s market cap. Several investors lost hope of recovering their loss until several rebuilding initiatives emerged.
However, LUNC’s recent price movements have shone a ray of light in the dark tunnel for the Terra Classic community. At press time, LUNC is still on the upward trajectory and has been so for over one week. 

Terra Classic (LUNC) price has increased by 10.04% over the past 24 hours, with an 11.59% price surge in the last seven days. Also, the token price has rallied 8.60% over the past 30 days. Terra Classic now trades at $0.00009638. 

LUNCUSD

LUNC’s price currently hovers at ).00009638 in the daily chart.  | Source: LUNCUSD price chart from TradingView.com
Ecosystem Improvements Are Pushing LUNC Price
LUNC’s price has been reacting to community buzz around notable upcoming ecosystem developments. For instance, the proposed Terra Classic v2.1.0 upgrade is only 24 hours away from commencement, while the LUNC Burn Army shared several tweet threads on June 8, reminding the community about the upgrade. The team highlighted the expected key improvements on the blockchain after the upgrade.
According to the LUNCBurnArmy, the upgrade will bring Terra Classic to parity with other blockchains, allowing developers and projects to start building on the chain again. The LUNC community is now counting down to the upgrade scheduled to go live on June 14 at 14:11 UTC.
This upgrade will also allow validators to earn a 5% commission for running nodes on the mainnet. The increased excitement as the community anticipates the upcoming v2.1.0 upgrade to parity must have rubbed off on Terra Classic (LUNC).
As one of the most anticipated events on the Terra ecosystem since the May 2022 disaster, v2.1.0 generated enough buzz to boost investor interest in LUNC. LUNC’s community and social sentiment has improved lately and is evident in the increased trading volume and LUNC staking.
Data from Mr. Diamondhandz1 shows that the number of staked LUNC hit 1 Trillion on June 10. This milestone achievement could be among the factors pushing LUNC’s price. Also, CoinMarketCap data shows that LUNC trading volume has risen by 106% over the past 24 hours while its market cap is up by 10.74%.
Featured image from Pixabay and chart from TradingView.com

Leituras Relacionadas

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.

marsbitHá 40m

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

marsbitHá 40m

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.

bitcoinistHá 1h

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

bitcoinistHá 1h

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.

marsbitHá 1h

GPT Designs GPT

marsbitHá 1h

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Há 1h

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

链捕手Há 1h

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.

marsbitHá 1h

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

marsbitHá 1h

Trading

Spot
Futuros
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow