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How NFT games are revolutionizing the industry

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How NFT games are revolutionizing the industry

by Gonzalo Wangüemert Villalba

4 September 2025

Introduction The open-source AI ecosystem reached a turning point in August 2025 when Elon Musk’s company xAI released Grok 2.5 and, almost simultaneously, OpenAI launched two new models under the names GPT-OSS-20B and GPT-OSS-120B. While both announcements signalled a commitment to transparency and broader accessibility, the details of these releases highlight strikingly different approaches to what open AI should mean. This article explores the architecture, accessibility, performance benchmarks, regulatory compliance and wider industry impact of these three models. The aim is to clarify whether xAI’s Grok or OpenAI’s GPT-OSS family currently offers more value for developers, businesses and regulators in Europe and beyond. What Was Released Grok 2.5, described by xAI as a 270 billion parameter model, was made available through the release of its weights and tokenizer. These files amount to roughly half a terabyte and were published on Hugging Face. Yet the release lacks critical elements such as training code, detailed architectural notes or dataset documentation. Most importantly, Grok 2.5 comes with a bespoke licence drafted by xAI that has not yet been clearly scrutinised by legal or open-source communities. Analysts have noted that its terms could be revocable or carry restrictions that prevent the model from being considered genuinely open source. Elon Musk promised on social media that Grok 3 would be published in the same manner within six months, suggesting this is just the beginning of a broader strategy by xAI to join the open-source race. By contrast, OpenAI unveiled GPT-OSS-20B and GPT-OSS-120B on 5 August 2025 with a far more comprehensive package. The models were released under the widely recognised Apache 2.0 licence, which is permissive, business-friendly and in line with requirements of the European Union’s AI Act. OpenAI did not only share the weights but also architectural details, training methodology, evaluation benchmarks, code samples and usage guidelines. This represents one of the most transparent releases ever made by the company, which historically faced criticism for keeping its frontier models proprietary. Architectural Approach The architectural differences between these models reveal much about their intended use. Grok 2.5 is a dense transformer with all 270 billion parameters engaged in computation. Without detailed documentation, it is unclear how efficiently it handles scaling or what kinds of attention mechanisms are employed. Meanwhile, GPT-OSS-20B and GPT-OSS-120B make use of a Mixture-of-Experts design. In practice this means that although the models contain 21 and 117 billion parameters respectively, only a small subset of those parameters are activated for each token. GPT-OSS-20B activates 3.6 billion and GPT-OSS-120B activates just over 5 billion. This architecture leads to far greater efficiency, allowing the smaller of the two to run comfortably on devices with only 16 gigabytes of memory, including Snapdragon laptops and consumer-grade graphics cards. The larger model requires 80 gigabytes of GPU memory, placing it in the range of high-end professional hardware, yet still far more efficient than a dense model of similar size. This is a deliberate choice by OpenAI to ensure that open-weight models are not only theoretically available but practically usable. Documentation and Transparency The difference in documentation further separates the two releases. OpenAI’s GPT-OSS models include explanations of their sparse attention layers, grouped multi-query attention, and support for extended context lengths up to 128,000 tokens. These details allow independent researchers to understand, test and even modify the architecture. By contrast, Grok 2.5 offers little more than its weight files and tokenizer, making it effectively a black box. From a developer’s perspective this is crucial: having access to weights without knowing how the system was trained or structured limits reproducibility and hinders adaptation. Transparency also affects regulatory compliance and community trust, making OpenAI’s approach significantly more robust. Performance and Benchmarks Benchmark performance is another area where GPT-OSS models shine. According to OpenAI’s technical documentation and independent testing, GPT-OSS-120B rivals or exceeds the reasoning ability of the company’s o4-mini model, while GPT-OSS-20B achieves parity with the o3-mini. On benchmarks such as MMLU, Codeforces, HealthBench and the AIME mathematics tests from 2024 and 2025, the models perform strongly, especially considering their efficient architecture. GPT-OSS-20B in particular impressed researchers by outperforming much larger competitors such as Qwen3-32B on certain coding and reasoning tasks, despite using less energy and memory. Academic studies published on arXiv in August 2025 highlighted that the model achieved nearly 32 per cent higher throughput and more than 25 per cent lower energy consumption per 1,000 tokens than rival models. Interestingly, one paper noted that GPT-OSS-20B outperformed its larger sibling GPT-OSS-120B on some human evaluation benchmarks, suggesting that sparse scaling does not always correlate linearly with capability. In terms of safety and robustness, the GPT-OSS models again appear carefully designed. They perform comparably to o4-mini on jailbreak resistance and bias testing, though they display higher hallucination rates in simple factual question-answering tasks. This transparency allows researchers to target weaknesses directly, which is part of the value of an open-weight release. Grok 2.5, however, lacks publicly available benchmarks altogether. Without independent testing, its actual capabilities remain uncertain, leaving the community with only Musk’s promotional statements to go by. Regulatory Compliance Regulatory compliance is a particularly important issue for organisations in Europe under the EU AI Act. The legislation requires general-purpose AI models to be released under genuinely open licences, accompanied by detailed technical documentation, information on training and testing datasets, and usage reporting. For models that exceed systemic risk thresholds, such as those trained with more than 10²⁵ floating point operations, further obligations apply, including risk assessment and registration. Grok 2.5, by virtue of its vague licence and lack of documentation, appears non-compliant on several counts. Unless xAI publishes more details or adapts its licensing, European businesses may find it difficult or legally risky to adopt Grok in their workflows. GPT-OSS-20B and 120B, by contrast, seem carefully aligned with the requirements of the AI Act. Their Apache 2.0 licence is recognised under the Act, their documentation meets transparency demands, and OpenAI has signalled a commitment to provide usage reporting. From a regulatory standpoint, OpenAI’s releases are safer bets for integration within the UK and EU. Community Reception The reception from the AI community reflects these differences. Developers welcomed OpenAI’s move as a long-awaited recognition of the open-source movement, especially after years of criticism that the company had become overly protective of its models. Some users, however, expressed frustration with the mixture-of-experts design, reporting that it can lead to repetitive tool-calling behaviours and less engaging conversational output. Yet most acknowledged that for tasks requiring structured reasoning, coding or mathematical precision, the GPT-OSS family performs exceptionally well. Grok 2.5’s release was greeted with more scepticism. While some praised Musk for at least releasing weights, others argued that without a proper licence or documentation it was little more than a symbolic gesture designed to signal openness while avoiding true transparency. Strategic Implications The strategic motivations behind these releases are also worth considering. For xAI, releasing Grok 2.5 may be less about immediate usability and more about positioning in the competitive AI landscape, particularly against Chinese developers and American rivals. For OpenAI, the move appears to be a balancing act: maintaining leadership in proprietary frontier models like GPT-5 while offering credible open-weight alternatives that address regulatory scrutiny and community pressure. This dual strategy could prove effective, enabling the company to dominate both commercial and open-source markets. Conclusion Ultimately, the comparison between Grok 2.5 and GPT-OSS-20B and 120B is not merely technical but philosophical. xAI’s release demonstrates a willingness to participate in the open-source movement but stops short of true openness. OpenAI, on the other hand, has set a new standard for what open-weight releases should look like in 2025: efficient architectures, extensive documentation, clear licensing, strong benchmark performance and regulatory compliance. For European businesses and policymakers evaluating open-source AI options, GPT-OSS currently represents the more practical, compliant and capable choice.  In conclusion, while both xAI and OpenAI contributed to the momentum of open-source AI in August 2025, the details reveal that not all openness is created equal. Grok 2.5 stands as an important symbolic release, but OpenAI’s GPT-OSS family sets the benchmark for practical usability, compliance with the EU AI Act, and genuine transparency.

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Euro Consolidates After the Impulse: Market Awaits Macro Data

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Euro Consolidates After the Impulse: Market Awaits Macro Data

The euro has moved into a phase of correction and consolidation ahead of key macroeconomic releases. In EUR/USD, a technical pullback is unfolding following the previous decline, while EUR/CAD continues a more extended corrective move within its medium-term structure. Market activity is easing as traders await important data from the euro area, the United States and Canada, which could determine the next directional move.

In the euro area, the focus is on Germany’s GDP figures, the GfK consumer climate index and business activity indicators. These releases will help assess the resilience of the region’s largest economy amid a slowdown in the manufacturing sector. Weak data would increase pressure on the euro, while more solid readings could support attempts at stabilisation.

In the United States, investors are monitoring developments in the mortgage market, upcoming comments from Federal Reserve officials and oil inventory data. Trade policy also remains a source of uncertainty. President Donald Trump announced the introduction of a temporary global tariff of 10% for 150 days, with the administration not ruling out a further increase to 15%. The postponement of harsher measures has slightly eased tensions, yet ongoing trade risks continue to influence currency markets, including the euro and commodity-linked currencies.

EUR/USD

After the resumption of the downward move in EUR/USD last week, buyers managed to find support near 1.1740. A retest of this level and a rebound towards 1.1840 helped establish the boundaries of the current sideways range. Technical analysis points to consolidative trading conditions. A sustained move above 1.1840 could pave the way for gains towards 1.1900–1.1920. A break below 1.1740 may trigger a fresh bearish impulse.

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Key events for EUR/USD:
– today at 09:00 (GMT+2): Germany GDP;
– today at 09:00 (GMT+2): Germany GfK Consumer Climate Index;
– today at 16:30 (GMT+2): speech by FOMC member Thomas Barkin.

EUR/CAD

EUR/CAD has been trading sideways for more than a month. The pair is testing 1.6180 as resistance and 1.6080 as support. A break above the upper boundary could lead to further gains towards 1.6200–1.6230. Conversely, a move below 1.6080 may open the way for a retest of the psychological 1.6000 level.

Key events for EUR/CAD:
– today at 15:30 (GMT+2): Canadian corporate profits;
– today at 17:30 (GMT+2): US crude oil inventories;
– tomorrow at 15:30 (GMT+2): Canadian wholesale sales.

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This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.

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Will Shiba Inu price drop as whale transfers 370B SHIB to exchange?

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Will Shiba Inu price drop as whale transfers 370B SHIB to exchange? - 1

Shiba Inu is back in focus after on-chain data showed a large holder moving hundreds of billions of tokens to a centralized exchange, raising fresh concerns about potential sell pressure.

Summary

  • On-chain data from Arkham shows a whale transferred roughly 370 billion SHIB to Binance and Bitget deposit addresses, raising concerns about potential sell pressure.
  • SHIB is trading near $0.00000601, holding short-term support at $0.00000580–$0.00000590, with resistance at $0.00000640 and $0.00000700.
  • Indicators remain cautious: the Awesome Oscillator is still negative but weakening, while the MFI around 44 signals limited buying momentum.

According to data from Arkham Intelligence, a whale address deposited roughly 370 billion SHIB to exchange wallets in a series of transactions over the past 24 hours. The transfers, routed to both Binance and Bitget deposit addresses, totaled several million dollars in value.

Will Shiba Inu price drop as whale transfers 370B SHIB to exchange? - 1

Large exchange inflows are often interpreted as a sign that a holder may be preparing to sell, as tokens moved off self-custody and onto trading platforms increase immediate circulating supply.

While it is not yet confirmed whether the whale intends to liquidate, the timing comes as SHIB continues to trade in a broader downtrend, adding weight to bearish sentiment.

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Shiba Inu price action and key levels

On the daily chart, SHIB is currently trading near $0.00000601, consolidating after a prolonged slide from January highs near the $0.00000900 region.

Will Shiba Inu price drop as whale transfers 370B SHIB to exchange? - 2
SHIB price analysis | Source: Crypto.News

Price recently bounced from the $0.00000580–$0.00000590 support zone, which has acted as a short-term floor. A decisive breakdown below this region could expose the next psychological support around $0.00000550, followed by deeper support near $0.00000500.

On the upside, immediate resistance sits near $0.00000640, where recent daily highs were rejected. Above that, stronger resistance is clustered around $0.00000700, a level that capped the mid-February rebound.

Bulls would need a sustained move above $0.00000700 to shift short-term structure back in their favor.

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Momentum indicators show tentative stabilization but no strong bullish reversal yet. The Awesome Oscillator (AO) remains slightly negative, though red histogram bars are shrinking, suggesting bearish momentum is weakening but not fully reversed.

The Money Flow Index (MFI 14) sits around 44, below the neutral 50 mark, indicating modest capital outflows and a lack of strong buying pressure.

Together, the indicators point to consolidation rather than immediate breakdown but they also fail to confirm a bullish shift.

If the 370B SHIB deposit translates into aggressive selling, pressure on the $0.00000580 support zone could intensify. A breakdown would likely accelerate downside momentum. However, if support holds and exchange inflows do not materialize into sustained sell volume, SHIB could remain range-bound between $0.00000580 and $0.00000640 in the near term.

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For now, whale activity adds uncertainty but the chart suggests bears still hold the broader structural advantage unless key resistance levels are reclaimed.

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MSTR tops list of most heavily shorted stocks, but don’t assume pure bearishness

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Highest short interest outstanding as a percentage of market cap (Goldman Sachs)

The market for Bitcoin-holder Strategy (MSTR) shares is among the most “heavily shorted,” a market slang term for dominance of bearish plays, according to FactSet and Goldman Sachs data. Yet the positioning may not reflect investor bias toward a continued price crash, per some observers.

According to the report released last week, bearish short bets on Strategy (MSTR) equaled 14% of its market capitalization of $34 billion at the time, making it the most shorted stock by that measure. Cryptocurrency exchange Coinbase (COIN) ranked fourth at 11% of its market cap. The report tracked positioning in stocks with market capitalization of over $25 billion.

This comes as Strategy is sitting on roughly a $7 billion unrealized loss on its bitcoin holdings. That figure, however, has no impact on the stock in the near term. Strategy began adding BTC to its balance sheet in 2020 and has since gobbled up 717,722 BTC, worth $47 billion. As of writing, its market cap stood closer at $42 billion, despite the stock falling 20% year-to-date.

One explanation for the elevated short interest offered by analysts is the basis trade – a strategy that seeks to profit from the price difference between two related markets. In this context, traders may bought bitcoin spot ETFs, like BlackRock’s IBIT, while simultaneously shorting the MSTR stock. to profit from a narrowing of MSTR’s premium to its BTC holdings narrows, plus any funding from paired futures if layered on, while staying market neutral.

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“I suspect a lot of this short interest is still MSTR / BTC basis trade. Jane Street, in particular, has recently acquired a conspicuously large IBIT position,” Brian Brookshire, specialist in bitcoin treasury companies, said.

According to recent 13F filings, Jane Street purchased more than 7 million shares of BlackRock’s iShares Bitcoin Trust. It also held a large position in MSTR.

If Brookshire’s instincts hold, Jane Street’s purchases of IBIT could be a part of the carry/basis trade, paired with short positions in MSTR.

So far this year, that trade would have not worked. The MSTR-to-IBIT ratio is up about 12%, meaning MSTR has outperformed IBIT on the downside. MSTR is down 20% year to date, while IBIT has fallen 27%.

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Highest short interest outstanding as a percentage of market cap (Goldman Sachs)

Highest short interest outstanding as a percentage of market cap (Goldman Sachs)

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Institutional ETF Flows Tilt Toward This Altcoin in February

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Solana ETF flows in February

Solana exchange-traded funds (ETFs) are diverging from broader crypto ETF trends this month. While demand for Bitcoin and Ethereum products has shown signs of cooling, Solana-linked funds have maintained steady inflows.

The shift comes amid heightened volatility in digital asset markets. With macro uncertainty weighing on investor sentiment, ETF flows may be offering a signal of where institutional capital is positioning in the short term.

Solana ETF Streak Stands Out in Volatile Crypto Market

According to data from SoSoValue, Solana ETFs have recorded consecutive inflows since February 10. As of February 24, the products have logged only three red days this month. Overall, the ETFs have pulled in $30.33 million. 

The streak stands out against the more uneven performance seen in larger crypto ETFs during the same period.

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Solana ETF flows in February
Solana ETF flows in February. Source: SoSoValue

Bitcoin ETFs have posted mixed results in February. Inflows were recorded on seven trading days this month. Ethereum ETFs have followed a similar pattern, reflecting inconsistent demand rather than sustained accumulation. 

Despite those positive sessions, cumulative flows remain deeply negative. So far this month, Bitcoin ETFs’ net outflows stand at $939.94 million. In addition, Ethereum ETFs recorded outflows of $490.58 million.

When compared to other altcoin products, Solana’s performance also appears relatively stronger. XRP-linked ETFs have experienced outflows on three trading sessions this month while recording zero flows on four days. 

Although the number of positive sessions is comparable, the consistency of Solana’s streak since mid-February remains notable.

Nonetheless, it is important to contextualize the data. In absolute dollar terms, inflows into Solana ETFs remain smaller than those seen in Bitcoin products. 

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Bitcoin and Ethereum ETFs continue to command the majority of institutional crypto exposure and overall capital allocation. However, consistency in flows can indicate relative resilience in demand during periods of broader uncertainty.

The steady inflows into Solana products suggest that some investors are maintaining or selectively increasing exposure to higher-beta assets, even as flagship crypto ETFs experience uneven demand. Still, the divergence may reflect short-term capital rotation rather than a structural shift in institutional positioning.

SOL Price Remains Under Pressure 

Despite the ETF inflows, Solana’s price performance has continued to reflect broader market weakness. Like most major digital assets, SOL has trended downward over the past month, declining 32.8%.

The altcoin saw a modest recovery today, rising more than 7% as total crypto market capitalization expanded by approximately $32 billion. At press time, SOL was trading at $82.15.

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Solana (SOL) Price Performance.
Solana (SOL) Price Performance. Source: BeInCrypto Markets

However, technical analysts remain cautious on the asset’s near-term outlook. Market commentator Alejandro suggested that Solana’s next downside target could be $45.

Whale Factor described the token as entering a high-probability “make or break” zone on the 4-hour chart. According to the analysis, SOL’s wedge formation is “reaching maximum exhaustion,” signaling a potential volatility squeeze at a critical inflection point.

The analyst outlined two possible scenarios:

“Bull Case: Clean break and retest of $82 targets the $97-100 macro resistance. Bear Case: Failure to hold the $78 support level opens the door for a retest of $68.”

Whether Solana will extend its recovery or face renewed downside pressure remains to be seen.

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Bitcoin Rebounds as Traders Debate Jane Street “10am Price Slam”

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Bitcoin Rebounds as Traders Debate Jane Street "10am Price Slam"

Bitcoin (BTC) sought to reclaim $65,000 as support into Wednesday’s Wall Street open as rumors swirled around US institutional pressure.

Key points:

  • Bitcoin bounces 2.5% as talk turns to alleged selling pressure from Wall Street trading company Jane Street.

  • Jane Street rebuts claims of crypto market manipulation during the 2022 bear market.

  • “Razor thin” order books boost BTC price volatility.

Bitcoiners debate Jane Street “10am price slam”

Data from TradingView tracked a BTC price rebound, taking BTC/USD to $66,300 on Bitstamp before the pair consolidated.

BTC/USD one-hour chart. Source: Cointelegraph/TradingView

Daily price gains remained at more than 2% at the time of writing, while crypto market participants became increasingly interested in potential deliberate BTC price suppression.

A theory circulating on social media revolved around secretive quantitative investment firm Jane Street, now subject to legal action by defunct crypto company Terraform Labs.

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Coordinated algorithmic selling of Bitcoin at 10am Eastern time daily, it alleged, provided the main impetus for months of BTC price downside beginning in October 2025.

Amid the ongoing legal proceedings, Jane Street may have been forced to suspend its trading strategy, leaving the market to adjust higher.

The Terraform Labs complaint makes specific reference to “market manipulation” that impacted crypto throughout 2022, the year in which Bitcoin put in its last bear market bottom of $15,600 in Q4.

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Jane Street told Cointelegraph that the accusations were “baseless, opportunistic claims.”

The 10am argument, meanwhile, failed to convince many. Crypto YouTuber Wise Advice was among them, suggesting that the theory was too simplistic to be valid.

BTC price versus “razor thin” liquidity

Commenting on the latest BTC price move, traders remained cautious.

Related: Bitcoin ETF sell-off is ‘purification’ of bull case, investor says

“$BTC is facing major resistance at $66k – from both the local range lows and the 4h trend,” trader Jelle wrote in his latest analysis on X. 

“Flipping that could spark short-term relief, but until that happens, the trend is clear. Don’t fight it.”

BTC/USD four-hour chart. Source: Jelle/X

Keith Alan, cofounder of trading resource Material Indicators, said that a “razor thin order book” on exchanges had contributed to the price rebound.

Overhead sell liquidity, he told X followers, had been pulled in advance of US President Donald Trump’s State of the Union address.

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The 24-hour crypto liquidations totaled $333 million at the time of writing, per data from CoinGlass, with shorts accounting for $213 million of that figure.

Crypto liquidation history (screenshot). Source: CoinGlass