2026-07-17 Sexta

Notícias de cripto - Página 4

Mantenha-se a par do mercado de cripto. Notícias em tempo real, análises, preços, histórias em alta e análise de especialistas — tudo num só lugar.

Bitcoin Shifts to Building a Bottom, with Selling Pressure from Long-Term Holders Significantly Easing

Bitcoin is transitioning into a basing phase, with significant selling pressure from long-term holders showing signs of easing. The market is testing overhead resistance, with Bitcoin responding more positively to favorable macro data like soft inflation reports than major equity indices. Its correlation with stocks is weakening while its inverse relationship with the US dollar strengthens, indicating a shift in primary drivers towards liquidity factors rather than risk sentiment. On-chain analysis reveals that long-term holder profit-taking has largely dried up, and the wave of capitulation selling from this cohort has peaked and begun to recede. Buyers successfully absorbed selling pressure at the June lows. Bitcoin currently trades between the network's average realized price (a support floor) and the short-term holder cost basis near $69k, which will be a key resistance level. A breakout above this level is needed to signal a more sustained recovery. In derivatives markets, traders are unwinding bearish bets, with put/call ratios falling and crash protection premiums declining. However, this futures and options positioning adjustment has not been accompanied by significant spot buying. US spot ETF outflows have slowed but not reversed. Volatility has compressed to low levels. In summary, the foundations for a bottom are forming: long-term holder selling is subsiding, demand absorbed the recent low, and the market is reacting to positive catalysts. However, confirmation is still lacking, requiring a spot-driven breakout and hold above the short-term holder cost basis around $69k.

Foresight NewsHá 17h

Bitcoin Shifts to Building a Bottom, with Selling Pressure from Long-Term Holders Significantly Easing

Foresight NewsHá 17h

OpenAI Officially Teaches You 8 Tricks to Master ChatGPT

OpenAI has released an updated guide with eight key strategies to get better results from ChatGPT: 1. **Use the latest model** (e.g., GPT-5.6 Sol) for best performance with prompt engineering. 2. **Provide clear, specific instructions**, detailing the desired content, format, style, and length. Avoid vague requests. 3. **Structure prompts effectively**: Place the core instruction at the beginning and use delimiters like `###` or `"""` to separate instructions from the text to be processed. 4. **Use examples and explanations** to clarify the exact output format and style you want. 5. **Adopt a stepwise approach**: Start with a zero-shot prompt (instruction only), then add a few examples (few-shot) if needed, and consider fine-tuning only as a last resort. 6. **Avoid vague or imprecise descriptions**. Use concrete terms (e.g., "3-5 sentences") instead of phrases like "keep it brief." 7. **Specify what to do, not just what to avoid**. After stating restrictions, guide the model toward the correct action. 8. **For code generation, use "leading words"** like `import` for Python or `SELECT` for SQL to steer the model into the correct pattern. Additionally, OpenAI's new "Generate Anything" feature can automatically create suitable prompts based on a simple description of your task. Mastering these techniques helps users get more accurate and useful outputs from ChatGPT.

marsbitHá 17h

OpenAI Officially Teaches You 8 Tricks to Master ChatGPT

marsbitHá 17h

GPT-5.6's IQ Breaks 130 Genius Threshold for the First Time, Outsmarting 99% of Humans

GPT-5.6 has reportedly achieved an IQ score of 136 on Tracking AI's proprietary offline test, surpassing the human "genius" threshold of 130 for the first time. This places it above an estimated 99% of humans in this specific metric. The test is designed to prevent memorization by using a private question bank. Multiple GPT-5.6 variants, including the vision model, consistently scored 136, leading competitors like Claude-5 Fable (130). User anecdotes suggest practical superiority over rivals in real-world coding and problem-solving tasks, such as building a physics simulation or a customer service app from a single prompt. While some speculate this approaches AGI for most users, the article notes IQ tests only measure a narrow slice of cognitive ability like pattern recognition. The significance lies in GPT-5.6's apparent ability to translate high test scores into effective task performance on novel, real-world problems.

marsbitHá 17h

GPT-5.6's IQ Breaks 130 Genius Threshold for the First Time, Outsmarting 99% of Humans

marsbitHá 17h

Altman Returns to Stanford and Admits Mistake: Outsourcing Thinking to AI, a Generation's Brains Are Atrophying

Sam Altman returned to Stanford University and admitted he was wrong about AI's impact on education. He predicted that after an initial phase of student cheating with ChatGPT, the education system would rapidly reform itself to teach more critical thinking. However, three and a half years later, while AI has advanced dramatically, teaching and assessment methods remain largely unchanged—still focused on memorization, standardized answers, and closed-book exams. Altman expressed deep concern that this disconnect is causing a "cognitive atrophy," where outsourcing thinking to AI erodes students' critical reasoning skills. Research supports this: grades have dropped in high-stakes exams after ChatGPT's introduction, and while assignment scores in writing and coding have inflated due to AI use, exam performance hasn't improved, indicating "outsourcing" rather than learning. He argues the problem lies in institutional inertia. The education system, built on the premise that tasks are time-consuming, hasn't adapted to a world where AI makes shortcuts effortless. Students are being evaluated by outdated standards, risking a generational gap in essential cognitive skills. Altman proposes a shift: education should move from testing memorization to fostering judgment, creativity, and the ability to ask better questions. Core practices like writing and programming remain vital not for their outputs, which AI can generate, but for the thinking process they train. The urgent need is to teach students not just to use AI, but to critically verify its outputs. Without reform, we risk a generation losing its capacity for independent thought.

marsbitHá 17h

Altman Returns to Stanford and Admits Mistake: Outsourcing Thinking to AI, a Generation's Brains Are Atrophying

marsbitHá 17h

Clearing Giant with $114 Trillion in Assets Tokenizes Securities, Has Crypto Won?

On July 15, the US securities settlement giant DTCC conducted its largest production-level test for tokenization, marking a significant shift from previous workarounds. The test involved approximately 40 institutions, including major players like JPMorgan, Citadel Securities, and State Street, as well as crypto-native firms such as Circle, Chainlink, and Ondo Finance. For the first time, DTCC, which custodies over $114 trillion in securities, directly created on-chain "digital twin" tokens for stocks, ETFs, and U.S. Treasuries held in its depository (DTC). These tokens share the same CUSIP identifiers and legal rights as the underlying assets. Key transactions included JPMorgan tokenizing an Invesco QQQ ETF to post as collateral at CME Group and DriveWealth settling a tokenized equity trade with Vanguard. The test paves the way for the official launch of the DTCC Tokenization Service in October. This move centralizes the issuance authority for tokenized traditional securities with the core market infrastructure itself. While projects like Ondo Finance (which participated in the test) will continue providing distribution and DeFi integration, their underlying collateral can now be DTCC-issued tokens, enhancing transparency and credit backing. The initiative aims to unlock liquidity in collateral by enabling 24/7 settlement and transfer across venues, a direct efficiency gain for DTCC. The test culminates years of DTCC's blockchain exploration, utilizing two key infrastructures: a private Hyperledger Besu chain for internal control and the Canton network (co-chaired by DTCC and Euroclear) for interoperable, privacy-focused transactions with external institutions. The event signals institutional tokenization moving into a new, mainstream phase led by traditional finance incumbents.

Foresight NewsHá 17h

Clearing Giant with $114 Trillion in Assets Tokenizes Securities, Has Crypto Won?

Foresight NewsHá 17h

Base Abandons Social Direction, Founder Admits Strategic Failure

Base, the Ethereum Layer-2 network often called the "L2 King," has formally ended its three-year "exploration era," with co-founder Jesse Pollak admitting its strategic focus on social applications was a mistake. In a recent statement, Pollak acknowledged that bets on social platforms like Farcaster and Zora, creator coins, and mini-apps failed to drive mainstream crypto adoption, leaving Base behind competitors in areas like perpetual contracts and payment solutions. He confirmed that Base's flagship app will now be managed by Cobie, a community leader, under Coinbase's oversight. Pollak's review highlighted Base's past struggles: leadership overemphasized a "creator economy" with limited real earnings for creators, development often followed trends set by Solana or BNB Chain, and a significant portion of on-chain activity was reportedly inflated. The vision of using social media to onboard billions to crypto clashed with the dominance of established Web2 platforms. Moving forward, Base will pivot to three core areas, as outlined by both Pollak and Coinbase CEO Brian Armstrong: **trading** (including tokenized stocks and memecoins), **payments** (leveraging global stablecoins), and **AI Agent services** (preparing for a machine-driven economy using crypto as native currency). This shift is seen as a return to crypto's fundamental strengths—finance and transactions. The strategic change coincides with personnel shifts at Coinbase, including the departure of executives like the Chief Legal Officer. Notably, Pollak himself has returned to hands-on coding. Furthermore, Coinbase reports that over 95% of its code is now AI-generated or assisted, with AI agents already performing work equivalent to about 1,200 employees—a trend expected to grow significantly, signaling how AI is reshaping the company's own operations as Base prepares to serve a future AI Agent economy.

Odaily星球日报Há 18h

Base Abandons Social Direction, Founder Admits Strategic Failure

Odaily星球日报Há 18h

Coinbase Stock Price Plummets 30% Year-to-Date, Why Isn't Wall Street Pessimistic?

Coinbase's stock has fallen nearly 30% year-to-date, yet Wall Street analysts like William Blair maintain an 'Outperform' rating. Despite lowering revenue and EBITDA forecasts for 2026/2027, their core view is that negative factors are already priced in. Key structural differences from the 2022 cycle—such as Bitcoin ETF adoption, institutional inflows, and clearer regulation—provide a better foundation. Analysts highlight Coinbase's diversification beyond spot trading, pointing to growth from its Base layer-2 network and a retail derivatives business generating over $200 million in annualized revenue. Technically, John Bollinger notes Bitcoin is forming a potential 'W' bottom pattern on daily charts, which could signal a major trend reversal if completed. On-chain data from Glassnode shows panic selling by long-term holders may have peaked, though sustained spot market buying is still needed to confirm a true bottom. While short-term price pressures remain, the consensus is that the current cycle's lows are being established, setting the stage for a potential recovery, with Coinbase's transaction volume expected to rebound over 30% in 2027 after a projected 44% drop this year.

Foresight NewsHá 18h

Coinbase Stock Price Plummets 30% Year-to-Date, Why Isn't Wall Street Pessimistic?

Foresight NewsHá 18h

Ethereum price prediction: Can ETH hold $1,900 after $57.7M in whale buying?

Ethereum (ETH) extended its recovery, decisively breaking above the $1,894.89 resistance and accelerating towards $1,923.82, with the $1,940-$1,950 zone now in focus. This bullish momentum was supported by lower-than-expected U.S. inflation and confirmed by a significant green volume spike. Despite a brief consolidation, the RSI remained above 70, indicating buyers are attempting to establish $1,894.89 as new support. The advance was fueled by significant short liquidations, with over $112.5 million liquidated in 24 hours—$92.2 million from shorts. A key liquidation cluster at $1,950 could trigger further upside if breached. Sustained buying pressure is needed to extend the recovery, with buyers currently absorbing selling pressure to maintain gains near $1,920.

ambcryptoHá 18h

Ethereum price prediction: Can ETH hold $1,900 after $57.7M in whale buying?

ambcryptoHá 18h

Wall Street Wolves, Stop Rushing into 2x and 3x Leveraged SK Hynix ETFs

The author warns of the significant risks associated with single-stock leveraged ETFs, using the recent case of the GraniteShares 2x Long LCID Daily ETF (LCDL) as a stark example. This ETF, which aimed to deliver 2x the daily return of Lucid Group (LCID) stock, was liquidated and delisted after LCID shares plunged 57% on a false bankruptcy rumor. Even though LCID recovered most of its losses by the close, LCDL investors lost everything with no chance of a rebound, illustrating how these products can be wiped out by short-term volatility. The article highlights that these high-risk ETFs have gained popularity among retail investors, particularly for betting on AI and memory chip stocks like SK Hynix. However, the amplified gains come with equally amplified risks. The potential for total, irreversible loss distinguishes these ETFs from holding the underlying stock, where investors can wait for a recovery. Citing growing systemic and social concerns, the piece notes that South Korean financial authorities are preparing to discuss stricter regulations for single-stock leveraged ETFs. This follows reports of social issues, including alleged suicides and a violent assault linked to major investment losses, underscoring how financial risk from these high-leverage products can spill over into societal problems.

marsbitHá 18h

Wall Street Wolves, Stop Rushing into 2x and 3x Leveraged SK Hynix ETFs

marsbitHá 18h

Wall Street Wolves, Stop Rushing into 2x, 3x SK Hynix ETFs

Title: "Wall Street Wolves, Stop Rushing into 2x, 3x SK Hynix ETFs" This article warns of the extreme risks associated with single-stock leveraged ETFs, particularly those targeting hot AI and semiconductor stocks like SK Hynix. These products amplify daily stock gains and losses by 2x or 3x. The piece highlights the recent case of the GraniteShares 2x Long LCID Daily ETF (LCDL), which was liquidated and delisted after Lucid Group's stock plunged over 57% on false bankruptcy rumors. Unlike a regular stock, which can potentially recover, the leveraged ETF was wiped out before the share price rebounded, leaving investors with total losses. It notes that such high-risk instruments are gaining popularity among retail investors chasing the AI and memory storage boom. This trend has caught regulatory attention, especially in South Korea, where government agencies are considering stricter oversight. Authorities are concerned that widespread use of these leveraged products, combined with social media investment hype, could amplify market volatility and transform financial losses into broader social problems, as hinted by recent extreme incidents linked to investment failures in the country.

Odaily星球日报Há 18h

Wall Street Wolves, Stop Rushing into 2x, 3x SK Hynix ETFs

Odaily星球日报Há 18h

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