Solana’s breakout and heavy short liquidations fuel bullish momentum, but overheating risks could spark volatility.
Toncoin and Quant are two altcoins that have witnessed a surge in whale transactions recently, something that could foreshadow volatility for their prices. Toncoin & Quant Have Seen A Spike In Whale Transaction Count In a new post on X, on-chain analytics firm Santiment has talked about the latest trend in the Whale Transaction Count for two altcoins: Toncoin (TON) and Quant (QNT). This indicator measures the total amount of transfers occurring on a given network that are carrying a value of more than $100,000. Generally, only the big-money investors or “whales” are capable of making transfers this large, so the metric’s value is considered to correspond to the activity from this cohort. These holders generally carry some degree of influence in the market, so whenever they are on the move, the market itself could experience fluctuations. This can make their activity worth keeping an eye on. Related Reading: Bitcoin’s Most Resolute Diamond Hands Are Only Growing Older, Data Shows Below is the chart shared by Santiment that shows how the Whale Transaction Count has changed for Toncoin and Quant over the last few months. As is visible in the graph, the Whale Transaction Count has seen a large spike for both Toncoin and Quant recently, suggesting the whales have been active on the networks. Interestingly, despite being the much bigger network in terms of market cap, TON’s spike has only amounted to a value of 3, while QNT has observed the metric touch the 24 mark. That said, the small value that Toncoin has witnessed is still high when compared to the past. In fact, only one spike in the last three months has been compared to this one. In contrast, Quant has seen a few spikes of a similar scale. Thus, it would appear that whales just tend to be less active on TON in general. As for what the spikes could imply for the altcoins, price volatility may be coming, if the past is to go by. “Historically, large spikes in $100K+ sized moves foreshadow price direction changes,” explains the analytics firm. These changes, however, can occur in either direction. Whale Transaction Count only counts up the number of moves that the large entities are making and doesn’t contain any information about the breakdown between buy and sell moves. Related Reading: Cardano Pushes Past $0.85: Falling Wedge Breakout Confirmed? As such, it’s always hard to tell whether a spike in whale activity is bullish or bearish for the asset’s value. The whales being active on the Toncoin and Quant networks could only suggest that some sort of sharp price action may be on the horizon. TON Price At the time of writing, Toncoin is floating around $3.1, down around 1.6% over the last seven days. Featured image from Dall-E, Santiment.net, chart from TradingView.com
A widely used Bitcoin technical analysis indicator suggested that BTC is on the verge of an “explosive price expansion” toward new all-time highs.
Ripple’s new custodial partnership with Spanish banking group BBVA integrates Ripple custody into BBVA’s retail crypto trading platform, enabling secure direct custody of Bitcoin and Ethereum and strengthening Ripple’s institutional
BitcoinWorld Unlocking Predictability: Thinking Machines Lab’s Revolutionary Push for AI Consistency In the fast-paced world of technology, where even the slightest unpredictability can have significant financial implications, the quest for reliable artificial intelligence has become paramount. For those invested in cryptocurrencies and other high-stakes digital assets, the stability and accuracy of underlying AI systems, from market analysis tools to decentralized application components, are not just desirable but essential. Imagine an AI predicting market trends or executing trades; its consistency is as crucial as the security of the blockchain itself. This is precisely the frontier that Mira Murati’s highly anticipated Thinking Machines Lab is set to revolutionize. The Critical Need for Consistent AI Models For too long, the AI community has largely accepted a fundamental challenge: the inherent nondeterminism of large language models (LLMs). If you’ve ever asked ChatGPT the same question multiple times, you’ve likely received a spectrum of answers, each slightly different. While this variability can sometimes mimic human creativity, it poses a significant hurdle for applications requiring absolute precision and reliability. Consider enterprise solutions, scientific research, or even advanced financial modeling – consistent outputs are not a luxury; they are a necessity. This is where the work of Thinking Machines Lab steps in, challenging the status quo and aiming to engineer a new era of predictable and trustworthy AI models . The problem of nondeterminism manifests in several ways: Lack of Reproducibility: Researchers struggle to replicate experimental results, slowing down scientific progress. Enterprise Adoption Challenges: Businesses hesitate to deploy AI in critical functions if they cannot guarantee consistent outcomes. Debugging Difficulties: Diagnosing errors in AI systems becomes exponentially harder when outputs vary randomly. Mira Murati, formerly OpenAI’s chief technology officer, has assembled an all-star team of researchers, backed by an astounding $2 billion in seed funding. Their mission, as unveiled in their first research blog post titled “Defeating Nondeterminism in LLM Inference” on their new platform “Connectionism,” is clear: to tackle this foundational problem head-on. They believe that the randomness isn’t an unchangeable fact of AI, but a solvable engineering challenge. Decoding Nondeterminism in LLM Inference The groundbreaking research from Thinking Machines Lab , specifically detailed by researcher Horace He, delves into the technical underpinnings of this nondeterminism. He argues that the root cause lies not in the high-level algorithms but in the intricate orchestration of GPU kernels. These small programs, which run inside powerful Nvidia computer chips, are the workhorses of AI inference – the process that generates responses after you input a query into an LLM. During LLM inference , billions of calculations are performed simultaneously across numerous GPU cores. The way these kernels are scheduled, executed, and their results aggregated can introduce tiny, almost imperceptible variations. These variations, when compounded across the vast number of operations in a large model, lead to the noticeable differences in outputs we observe. Horace He’s hypothesis is that by gaining meticulous control over this low-level orchestration layer, it is possible to eliminate or significantly reduce this randomness. This isn’t just about tweaking a few parameters; it’s about fundamentally rethinking how AI computations are managed at the hardware-software interface. This approach highlights a shift in focus: From Algorithms to Orchestration: Moving beyond model architecture to the underlying computational execution. Hardware-Aware AI: Recognizing the profound impact of hardware-software interaction on model behavior. Precision Engineering: Applying rigorous engineering principles to AI inference processes. This level of control could unlock unprecedented reliability, making AI systems behave more like traditional deterministic software, where the same input always yields the same output. Why AI Consistency is a Game-Changer for Innovation The implications of achieving true AI consistency are vast and transformative, extending far beyond simply getting the same answer twice from ChatGPT. For enterprises, it means building trust in AI-powered applications, from customer service chatbots that always provide uniform information to automated financial analysis tools that generate identical reports given the same data. Imagine the confidence businesses would have in deploying AI for critical decision-making processes if they could guarantee reproducible outcomes. In the scientific community, the ability to generate reproducible AI responses is nothing short of revolutionary. Scientific progress relies heavily on the ability to replicate experiments and verify results. If AI models are used for data analysis, simulation, or hypothesis generation, their outputs must be consistent for findings to be considered credible and build upon. Horace He further notes that this consistency could dramatically improve reinforcement learning (RL) training. RL is a powerful method where AI models learn by receiving rewards for correct actions. However, if the AI’s responses are constantly shifting, the reward signals become noisy, making the learning process inefficient and prolonged. Smoother, more consistent responses would lead to: Faster Training: Clearer reward signals accelerate the learning curve. More Robust Models: Training on consistent data leads to more stable and reliable AI. Reduced Data Noise: Eliminating variability in responses cleans up the training data, improving overall model quality. The Information previously reported that Thinking Machines Lab plans to leverage RL to customize AI models for businesses. This suggests a direct link between their current research into consistency and their future product offerings, aiming to deliver highly reliable, tailor-made AI solutions for various industries. Such developments could profoundly impact sectors ranging from healthcare and manufacturing to finance and logistics, where precision and reliability are paramount. Thinking Machines Lab: A New Era of Reproducible AI The launch of their research blog, “Connectionism,” signals Thinking Machines Lab ‘s commitment to transparency and open research, a refreshing stance in an increasingly secretive AI landscape. This inaugural post, part of an effort to “benefit the public, but also improve our own research culture,” echoes the early ideals of organizations like OpenAI. However, as OpenAI grew, its commitment to open research seemingly diminished. The tech world will be watching closely to see if Murati’s lab can maintain this ethos while navigating the pressures of a $12 billion valuation and the competitive AI market. Murati herself indicated in July that the lab’s first product would be unveiled in the coming months, designed to be “useful for researchers and startups developing custom models.” While it remains speculative whether this initial product will directly incorporate the techniques from their nondeterminism research, the focus on foundational problems suggests a long-term vision. By tackling core issues like reproducibility, Thinking Machines Lab is not just building new applications; it’s laying the groundwork for a more stable and trustworthy AI ecosystem. The journey to create truly reproducible AI is ambitious, but if successful, it could solidify Thinking Machines Lab’s position as a leader at the frontier of AI research, setting new standards for reliability and paving the way for a new generation of dependable intelligent systems. The Road Ahead: Challenges and Opportunities for Thinking Machines Lab The venture of Thinking Machines Lab is not without its challenges. Operating with a $12 billion valuation brings immense pressure to deliver not just groundbreaking research but also commercially viable products. The technical hurdles in precisely controlling GPU kernel orchestration are formidable, requiring deep expertise in both hardware and software. Furthermore, the broader AI community’s long-standing acceptance of nondeterminism means that TML is effectively challenging a deeply ingrained paradigm. Success will require not only solving the technical problem but also demonstrating its practical benefits convincingly to a global audience. However, the opportunities are equally immense. By solving the problem of AI consistency, Thinking Machines Lab could become the standard-bearer for reliable AI, attracting partners and customers across every industry. Their commitment to sharing research publicly, through platforms like Connectionism, could foster a collaborative environment, accelerating innovation across the entire AI ecosystem. If they can successfully integrate their research into products that make AI models more predictable, they will not only justify their valuation but also fundamentally alter how businesses and scientists interact with artificial intelligence, making it a more dependable and indispensable tool for progress. In conclusion, Thinking Machines Lab’s bold foray into defeating nondeterminism in LLM inference represents a pivotal moment in AI development. By striving for greater AI consistency , Mira Murati and her team are addressing a core limitation that has hindered broader AI adoption in critical sectors. Their focus on the intricate details of GPU kernel orchestration demonstrates a profound commitment to foundational research, promising a future where AI models are not just powerful but also reliably predictable. This endeavor has the potential to unlock new levels of trust and utility for artificial intelligence, making it a truly revolutionary force across all industries, including the dynamic world of digital assets and blockchain technology. To learn more about the latest AI models trends, explore our article on key developments shaping AI features. This post Unlocking Predictability: Thinking Machines Lab’s Revolutionary Push for AI Consistency first appeared on BitcoinWorld and is written by Editorial Team
The bug impacted some remote procedure call (RPC) nodes, causing them to fall out of sync, but did not impact onchain block production.
ChatGPT challenger Perplexity AI predicts that XRP, Pepe, and Shiba Inu could generate substantial gains for investors as the year heads into the holiday season. Market activity seems to support this outlook. At the end of last month, Bitcoin reached an all-time high of $124,128, surpassing its earlier record of $122,838 set just weeks prior. The rally, however, lost momentum when the Bureau of Labor Statistics reported higher-than-expected U.S. inflation for July. On the regulatory front, President Trump signed the GENIUS Act, the first U.S. law specifically addressing stablecoins, mandating full reserve backing. Simultaneously, the SEC rolled out Project Crypto , a broad initiative aimed at modernizing securities frameworks and offering blockchain firms clearer regulatory guidance. With these policy shifts and bullish market signals, many analysts anticipate that meme coins and altcoins could rival or even exceed the mania of 2021, with XRP, Pepe, and Shiba Inu poised to benefit most if Perplexity’s outlook plays out. XRP (Ripple): Perplexity AI Predicts 5× Upside, With $15 Target Possible Perplexity predicts that XRP ($XRP) could climb to $10 by the end of 2025, quintupling its current price of $3. The coin has already displayed strength, hitting $3.65 on July 18, breaking above its 2018 high of $3.40, before sliding roughly 18% to where it trades today. Ripple continues to expand internationally. In 2024, the UN Capital Development Fund recognized XRP as a viable solution for cross-border payments in emerging markets. Earlier this year, Ripple finally closed its long-standing battle with the SEC after the regulator dropped its lawsuit. This reaffirmed the 2023 ruling that XRP’s retail transactions are not securities sales, a landmark decision for major altcoins. If momentum continues, Perplexity suggests a base case of $3.30–$5.50, with a bullish run potentially carrying it to $15, should the Trump administration make good on its word to provide clearer industry guidance. Another catalyst would be the US SEC’s approval of spot XRP ETFs. Technical indicators remain favorable: the RSI is uptrending from 54, signaling growing buying that could take it up to $4 by October. Over the past year, XRP has jumped 456%, eclipsing Bitcoin’s 98% and Ethereum’s 86%. Shiba Inu (SHIB): Perplexity AI Predicts Potential 8× Surge for Ethereum-Based Meme Coin Launched in August 2020, Shiba Inu ($SHIB) has consistently held its spot as Dogecoin’s strongest competitor, now boasting a market capitalization above $7.6 billion. Currently priced around $0.00001303 after a modest 0.2% dip in the last 24 hours, SHIB has retained value better than Dogecoin and Pepe, which overnight fell 1.5% and 2.1% respectively. For comparison, the overall meme coin sector (worth $80.2 billion) saw an overnight 0.2% dip. SHIB is also breaking out of two bullish chart patterns this year: a falling wedge and a bull flag. A decisive breakout above $0.000025 could confirm Perplexity’s bullish year-end target range of $0.00005–$0.00008, representing a potential 5× to 8× rally from current levels. The RSI sits at 48, reflecting the recent sell-off, but this is likely to reverse as inflation-driven volatility subsides. Beyond its meme status, Shiba Inu now runs Shibarium , a Layer-2 scaling network that enables faster, cheaper transactions and supports decentralized applications. Recent privacy features further set it apart from competitors. Pepe ($PEPE): Perplexity Predicts Up to 4× Gains for Leading Non-Doge Meme Coin Debuting in April 2023, Pepe ($PEPE) quickly climbed into the top three meme coins, with a current market capitalization of $4.4 billion, the largest non-canine meme coin. Despite stiff competition, Pepe maintains relevance thanks to strong liquidity and an engaged community. Elon Musk has even hinted at holding Pepe alongside Dogecoin, dropping playful references on X. At $0.00001053, Pepe slightly underperformed the broader $80 billion meme sector. However, in the last seven days it rose 7%, outperforming Dogecoin, Bitcoin, Ethereum, XRP and many other top cryptos. Clearing resistance around $0.000018–$0.000022 could pave the way for a move toward $0.00003 by mid-fall. In a bullish environment, Perplexity suggests Pepe could climb as high as $0.000035, delivering slightly more than 3x returns for investors. The chart reveals a descending wedge pattern forming between November and March, a historically bullish signal. With clearer regulatory guardrails emerging, Pepe could be well positioned for a breakout. Maxi Doge (MAXI): Dogecoin’s Shredded Degen Cousin For those looking at new projects outside of Perplexity’s main forecasts, Maxi Doge ($MAXI) offers a fresh spin on meme investing, branding itself as Dogecoin’s amped-up and long-overlooked cousin. As Dogecoin has matured into a multibillion-dollar asset that often tracks Bitcoin and Ethereum, its price swings have become less dramatic compared to its 2021 run. For traders chasing higher-risk, higher-reward meme plays, Maxi Doge is quickly catching on, already raising close to $2 million just weeks into its launch. Built on the ERC-20 standard, MAXI is focused on community building, with plans to grow Telegram and Discord channels, run trading contests, and partner with other projects. Of its 150.24 billion total tokens, 25% are dedicated to the Maxi Fund for marketing and collaborations. Staking is also available, with current yields at an eye-catching 158% APY, though rates will decline as participation increases. The presale price is currently $0.0002565 and is set to rise within the next two and a half days. Investors can join via the Maxi Doge website using wallets like MetaMask or Best Wallet . Stay updated through Maxi Doge’s official X and Telegram pages. Visit the Official Website Here The post Perplexity AI Predicts the Price of XRP, Shiba Inu and Pepe by the End of 2025 appeared first on Cryptonews .
Ripple signs new deal to expand custodial services across Europe
As the combined capitalization of all cryptos reclaims $4 trillion mark following recent setbacks, here are three of the very best meme coins under $1 that could be strong contenders for investors. Below, we outline why these tokens are attracting attention and what makes them stand out as some of the most compelling low-cost meme coin opportunities right now. Maxi Doge ($MAXI): Dogecoin’s Supercharged Successor Riding a Million-Dollar Wave A new rival to Dogecoin is making noise with its own twist. Say hello to Maxi Doge ($MAXI) , the bulked-up, long-overlooked relative of the OG meme token. Dogecoin’s massive market capitalization now ties its price performance closely to leading cryptos like Bitcoin and Ethereum. While still classified as a meme coin, its volatility has tempered compared to its explosive 2021 rally. For traders chasing higher-risk meme plays with more dramatic upside potential, Maxi Doge ($MAXI) is quickly gaining traction, already raising $2 million just weeks after launch. Operating as an ERC-20 token, MAXI places heavy emphasis on its community. The team is actively building Telegram and Discord hubs with trading competitions and collaborative events to strengthen engagement. Out of a total supply of 150.24 billion tokens, 25% is reserved in a “Maxi Fund” for marketing campaigns and partnerships. Holders can also stake MAXI, with APYs reaching as high as 159% (though these returns will inevitably adjust as participation grows). The presale price sits at $0.000256, but will increase slightly within the next two days. Investors can purchase directly through the Maxi Doge website using wallets such as MetaMask or Best Wallet . Follow Maxi Doge’s official X and Telegram pages. Visit the Official Website Here PEPENODE ($PEPENODE): The New Presale that’s Reinventing Meme Cryptos with Mine-to-Earn has Already Raised $1 Million One of the freshest ERC-20 meme coin launches, PEPENODE ($PEPENODE) , has quickly gained buzz thanks to its unusual mechanics and early fundraising success. Despite launching just two weeks ago, the project has already secured nearly $1 million in presale contributions, reflecting rapidly growing interest. PEPENODE brands itself as the first “mine-to-earn” cryptocurrency. Instead of relying solely on staking, the project gamifies rewards by allowing holders to build virtual mining nodes. The more nodes a user creates with their PEPENODE tokens, the larger their staking returns, creating a cycle that rewards accumulation and participation. This innovative staking approach could drive long-term engagement and steady token demand. Additionally, those that stake during the presale can claim APY of 1,445%, although this declines as the number of pool participants grows, so interested investors have to move quickly to maximize returns. Currently, tokens are available via the PEPENODE website at $0.0010533, with incremental price hikes every few days until the presale ends. Early buyers gain the best entry point. Follow PEPENODE on X and Telegram for updates. Visit the Official Website Here Wall Street Pepe ($WEPE): Empowering Retail Traders of Cryptos with Trading Community, Currently a Thousandth of $1 Wall Street Pepe ($WEPE) , a meme coin with a trading community focus, first rolled out on Ethereum earlier this year — and now it’s preparing to debut on Solana. Since late May, the Ethereum version of WEPE has skyrocketed over 250%. Since Monday, it’s intraday price gains have outperformed heavyweights like Shiba Inu ($SHIB) and Pepe ($PEPE). Even on today’s slight downturn, it dipped only 0.4%, in line with Dogecoin and retaining value better than its aforementioned rivals. Wall Street Pepe’s concept is simple but powerful: merge meme coin appeal with a trading-centric ecosystem. WEPE holders gain access to community hubs that provide signals, insights, and tools for collective trading strategies. The Solana launch doesn’t alter WEPE’s overall supply but adds a bullish twist: every Solana-based WEPE purchased triggers a 1:1 burn of the ERC-20 version via smart contracts. This widens the token’s distribution while keeping supply balanced. By expanding onto Solana, WEPE benefits from faster transactions, lower fees, and better scalability, while unlocking access to a broader audience of investors. The Solana token can be ordered for $0.001 through the official Wall Street Pepe site and will list on exchanges soon. Follow Wall Street Pepe on X and Telegram for updates. Visit the Official Website Here The post 3 Cryptos Under $1 to Turn $100 into $10,000 – 10 September appeared first on Cryptonews .
Altcoin season often takes shape through tokens that capture unique flows of capital. This week, three assets are standing out in distinct ways. Pump.fun has continued to climb on the back of steady memecoin creation. Mantle has benefited from new futures products and exchange campaigns. Avalanche is drawing attention for partnerships that extend into mainstream industries. The combined picture shows how different categories of tokens can rise at the same time. Retail participation, speculative trading, and enterprise adoption each serve as drivers. This creates a varied altseason environment where no single factor explains market direction, but each token draws strength from its own sources. Pump.fun (PUMP): Launch Platform Fuels Seven-Day Rally Pump.fun currently trades near $0.0056 , giving it a market capitalization close to $2 billion and daily turnover of about $480 million, according to CoinMarketCap. Circulating supply stands at 354 billion tokens out of a total allocation of 1 trillion. Price has advanced around 16% over the last day and more than 38% during the past week. The token is linked to a Solana-based platform that lets users create and trade new tokens instantly. This model has kept transaction counts high and maintained strong liquidity. Lower platform fees introduced in recent weeks have further encouraged usage. That combination of constant launches and cheaper creation costs has reinforced PUMP’s move upward, making it one of the more active tokens in current altcoin trading. Mantle (MNT): Exchange Support Drives Participation Mantle currently trades around $1.48, with a market capitalization of $4.8 billion and a circulating supply near 3.2 billion tokens. Daily trading volume has climbed alongside price, which is up 12% over 24 hours and 32% over the past week. Mantle Price (Source: CoinMarketCap) The main catalyst has been broader exchange support. Coinbase International recently introduced perpetual futures linked to Mantle, opening access to a new set of traders. At the same time, Bybit ran promotions tied to Mantle pairs, adding liquidity incentives. These steps have increased both speculation and hedging, which explains the spike in trading activity. Chart signals indicate Mantle has been trading near resistance zones, but elevated demand has kept momentum intact for now. Avalanche (AVAX): Partnership News Adds to Market Strength Avalanche now trades close to $29 , with market capitalization above $12 billion and daily turnover near $1.6 billion. Circulating supply stands at about 422 million tokens. The token has gained 12% in the last day and 15% over the past week. The recent lift has been linked to collaboration announcements. Toyota revealed work with Avalanche technology in connection with blockchain-based mobility programs. This has drawn renewed attention to Avalanche’s efforts to expand beyond DeFi into enterprise applications. Technical indicators show AVAX holding above prior resistance at $27, suggesting support from both news and trader positioning. Altcoin Season Outlook Pump.fun, Mantle, and Avalanche are moving for separate reasons. Pump.fun thrives on its role in Solana memecoin creation. Mantle benefits from futures listings and exchange-driven activity. Avalanche builds traction from enterprise partnerships and steady trading support. Altcoin season is unfolding through these different paths. Each token illustrates how liquidity can gather around specific narratives or use cases. While overall market conditions remain cautious, the ability of these tokens to draw attention shows how selective rotations continue to define altseason. The post Altcoin Season Develops Through Pump.fun, Mantle, and Avalanche appeared first on Cryptonews .