Models Can Also "Nest"? MiniMax Releases M2.7: The First Domestic Large Model Deeply Involved in Self-Iteration

marsbit2026-03-18 tarihinde yayınlandı2026-03-18 tarihinde güncellendi

Özet

Artificial intelligence is evolving from monthly updates to self-evolution. On March 18, MiniMax released its first new model version deeply involved in its own iteration—MiniMax M2.7. This marks a new stage in model development: large models are no longer solely trained by human programmers but have begun to "train themselves." The core breakthrough of MiniMax M2.7 lies in its strong autonomous construction capability. It can independently build complex Agent Harness (intelligent agent testing frameworks) and, relying on underlying capabilities such as Agent Teams, complex Skills, and Tool Search tools, complete highly complex productivity tasks autonomously. In simple terms, M2.7 is not just a smarter conversational agent but also a "digital engineer" capable of self-diagnosis and self-optimization. This "self-participatory iteration" model will significantly enhance the model’s logical reasoning and tool invocation accuracy when facing unknown complex tasks. Currently, this self-evolving MiniMax M2.7 model has been fully launched on the MiniMax Agent platform and open platform. As large models begin to deeply participate in their own "growth" process, the ceiling of AI may be raised once again.

The evolution speed of artificial intelligence is transitioning from "monthly updates" to "self-evolution." On March 18, MiniMax officially released its first new version model deeply involved in iterating itself—MiniMax M2.7. This marks a new stage in model development: large models are no longer solely fed by human programmers but have begun to learn to "guide themselves."

According to reports, the core breakthrough of MiniMax M2.7 lies in its powerful autonomous construction capability. It can independently build complex Agent Harness (intelligent agent testing frameworks) and, relying on underlying capabilities such as Agent Teams (intelligent agent collaboration), complex Skills, and Tool Search tool, independently complete highly complex productivity tasks.

Simply put, M2.7 is not just a smarter conversationalist but also a "digital engineer" capable of self-diagnosis and self-optimization. This "self-participatory iteration" model will significantly enhance the model's logical reasoning limits and tool invocation accuracy when facing unknown complex tasks.

Currently, this MiniMax M2.7 model, equipped with self-evolution genes, has been fully launched on the MiniMax Agent platform and open platform. As large models begin to deeply participate in their own "growth" process, the ceiling of AI may be raised once again.

Meanwhile, the AI computing power and application market are also seeing frequent developments. LuChen Technology announced the completion of a Series B financing round worth hundreds of millions of yuan, with its overseas revenue share soaring to 79%; meanwhile, due to a surge in call volumes, some of Alibaba Cloud's AI computing power products have reportedly seen price increases. Amid the interplay of technological iteration and market fluctuations, the AI track in 2026 is becoming increasingly urgent and full of variables.

İlgili Sorular

QWhat is the name of the new model released by MiniMax that is capable of deep self-iteration?

AThe new model is called MiniMax M2.7.

QWhat is the core breakthrough of the MiniMax M2.7 model according to the article?

AIts core breakthrough is its strong autonomous construction capability, allowing it to build complex Agent Harness and complete highly complex productivity tasks independently.

QWhat specific abilities does the M2.7 model use to complete complex tasks?

AIt uses abilities such as Agent Teams (agent collaboration), complex Skills, and Tool Search tool to complete tasks.

QOn which platforms has the MiniMax M2.7 model been fully launched?

AIt has been fully launched on the MiniMax Agent platform and the open platform.

QBesides the MiniMax announcement, what other AI market dynamics are mentioned in the article?

AThe article mentions that LuChen Technology completed a Series B financing of hundreds of millions of yuan, and Alibaba Cloud increased prices for some AI computing products due to a surge in usage.

İlgili Okumalar

The AI Agent Era Accelerates Its Arrival: Questflow Defines a New Paradigm of Financial Intelligence with On-Chain AI Brokerage

The AI Agent era is accelerating, with the CB Insights AI 100 list highlighting global investment confidence. The focus has shifted from whether AI works to its speed of deployment and ability to manage complex workflows, with autonomous AI Agents driving this transformation. At the forefront is Questflow, a Singapore-based startup redefining financial intelligence through its on-chain AI brokerage. Unlike tools that merely provide data dashboards, Questflow deploys AI Agents that proactively scan markets, form judgments, and execute trades via a conversational interface—operating 24/7 without requiring manual confirmation for each decision. This embodies the new AI paradigm of agents capable of executing multi-step workflows autonomously. Questflow's mission is to democratize institutional-grade trading intelligence. Historically reserved for the ultra-wealthy, this capability is now accessible starting from just $1 through Questflow's "AI Clone + Copy Trade" model. The platform charges only a 1% execution fee, aligning its incentives directly with users and eliminating traditional management or performance fees. The timing is opportune, aligning with key trends identified by CB Insights: the scalable deployment of AI Agents, accelerated AI adoption in financial services, and the maturation of on-chain infrastructure. With robust liquidity on platforms like Hyperliquid and Polymarket, alongside advancements in AI reasoning and non-custodial wallet security, Questflow is positioned to merge the roles of broker, fund, and exchange into a single, accessible platform for millions.

链捕手12 dk önce

The AI Agent Era Accelerates Its Arrival: Questflow Defines a New Paradigm of Financial Intelligence with On-Chain AI Brokerage

链捕手12 dk önce

Why Pricing Social Interactions is Doomed to Fail?

Titled "Why Putting a Price on Social Interaction Is Doomed to Fail," this article critiques attempts to monetize social networks directly through SocialFi models, arguing their inevitable failure stems from a fundamental misunderstanding of media dynamics. Using Marshall McLuhan's theory of "hot" and "cold" media, the author posits that social networks are inherently "cold" media. Their value isn't contained in individual posts but is co-created through user participation, interpretation, and fragmented, ongoing interaction (e.g., replies, shares). This ambiguity and need for user involvement are core to their function. The article asserts that SocialFi projects like Friend.tech failed because introducing real-time, tradable financial pricing (a definitive "hot" signal) into this "cold" environment doesn't add a layer—it replaces the medium's essence. The unambiguous price signal overshadows and nullifies the nuanced, participatory social signal. Users become traders, not participants, and when speculative profits vanish, the underlying social ecosystem—never genuinely cultivated—collapses entirely. This principle extends beyond crypto. The author argues platforms like Twitter have gradually "heated up" through metrics (likes, retweets counts, algorithmically defined value), shifting users from participants to performers and eroding organic engagement. The solution isn't to abandon capital but to manage its entry point. Successful models like Substack, Patreon, or Bandcamp allow capital to "condense" at specific, isolated nodes (e.g., subscriptions, one-time payments) without permeating and "heating" every social interaction. They preserve the core "cold," participatory medium while enabling monetization at designated boundaries. The NFT boom and bust serves as a stark parallel: the ancient "cold" medium of collecting (valued for story, community, gradual accumulation) was rapidly destroyed by platforms that introduced real-time floor prices, rarity scores, and trading dashboards, transforming collectors into speculators and vaporizing cultural value when prices fell. The core lesson: "Liquidity equals heat." Injecting high liquidity and definitive pricing into a "cold" participatory medium doesn't optimize it; it fundamentally alters and destroys its value-creating mechanism. The future lies not in pricing every social gesture but in finding precise, non-invasive points for capital to condense without overheating the entire ecosystem.

marsbit20 dk önce

Why Pricing Social Interactions is Doomed to Fail?

marsbit20 dk önce

Trump Media’s Crypto Bet Implodes With Massive $406M Quarterly Loss

Trump Media & Technology Group, parent company of Truth Social, reported a massive $406 million net loss in Q1 2026, sharply up from $31.7 million a year earlier. The collapse was driven primarily by $370 million in unrealized losses from digital asset investments. These include a $61 million loss on 756 million Cronos tokens and a nearly $500 million gap on 9,542 Bitcoin purchased near the 2025 market peak, though Bitcoin's recent recovery has reduced that paper loss. Adding to turmoil, CEO Devin Nunes resigned in late April. Meanwhile, the company's core media revenue was only $871,200, a minimal increase. Despite the financial losses, the company generated $18 million in operating cash flow by selling options on its pledged Bitcoin holdings. Its stock, once valued at over $97, now trades around $9, reflecting a more than 90% decline from its 2022 peak.

bitcoinist26 dk önce

Trump Media’s Crypto Bet Implodes With Massive $406M Quarterly Loss

bitcoinist26 dk önce

Bitcoin Volatility Returns as Price Tests Critical Indicator Level

Bitcoin experienced significant volatility, briefly surpassing $82,000 before falling back to around $80,000. This triggered over $400 million in liquidations within 24 hours, though the price later recovered moderately above $81,000. The key focus is Bitcoin's approach to the critical 200-day Exponential Moving Average (EMA), a major resistance level near $82,580 that has repeatedly capped price advances since November 2025. Analyst Brett suggests a sustained break above this level could signal the end of the bear market. However, failure to breach it has historically led to sharp declines, with an average drop of 30% from this rejection zone. If this pattern repeats, Bitcoin's price could potentially fall to around $56,600 from current levels. Despite the price pressure, cryptocurrency investment products saw a sixth consecutive week of inflows totaling $4.9 billion, supported by positive sentiment around US crypto legislation.

TheNewsCrypto51 dk önce

Bitcoin Volatility Returns as Price Tests Critical Indicator Level

TheNewsCrypto51 dk önce

Jensen Huang's CMU Speech: In the AI Era, Don't Just Watch, Build

Jensen Huang, CEO of NVIDIA and a first-generation immigrant, delivered the commencement address to Carnegie Mellon University's class of 2026. He shared his personal journey from a humble background to founding NVIDIA, emphasizing resilience, learning from failure, and the responsibility that comes with leadership. Huang framed the present moment as the dawn of the AI revolution, a shift he believes is more profound than previous computing waves. He described AI as fundamentally resetting computing—moving from human-written software to machines that understand, reason, and use tools. This will create a new industry for generating intelligence and transform every sector. While acknowledging AI's potential to automate tasks and displace some jobs, Huang distinguished between the *tasks* of a job and its core *purpose*. He argued AI will augment human capability, not replace humans. The real risk, he stated, is not AI itself, but people being left behind by those who effectively use AI. He presented AI as a generational opportunity for massive infrastructure investment—in chip factories, data centers, energy grids, and advanced manufacturing—that could re-industrialize nations like the U.S. and bridge the digital divide by making computing and intelligent tools accessible to all. Huang called for a balanced approach: advancing AI safely and responsibly, establishing prudent policies, ensuring broad access, and encouraging universal participation. He urged the graduates not to fear the future but to engage with optimism and ambition, reminding them of CMU's motto, "My heart is in the work." His core message was clear: this is their moment to actively build and shape the AI-powered future, not merely observe it.

marsbit1 saat önce

Jensen Huang's CMU Speech: In the AI Era, Don't Just Watch, Build

marsbit1 saat önce

İşlemler

Spot
Futures
活动图片