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

marsbitОпубліковано о 2026-03-18Востаннє оновлено о 2026-03-18

Анотація

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.

Пов'язані питання

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.

Пов'язані матеріали

Bitcoin Withdrawals Continue: 8 Years of Storage in a Coldcard Cold Wallet Ended in Zero

Coldcard Hardware Wallet Hacked: Losses Mount Due to Vulnerable Seed Generation A critical vulnerability in Coldcard hardware wallets has led to a continued wave of fund thefts. According to Galaxy Research, the total stolen has reached 1,367.05 BTC (approx. $88.6 million) from 4,585 addresses, a significant increase from the initial 594.5 BTC reported on July 30, 2026. Most of the stolen funds remain on the attackers' addresses. The issue is not with the current firmware, which Coinkite has updated, but with seed phrases generated on vulnerable devices between March 2021 and the release of fixed firmware versions. Due to a programmer error, devices switched from using a hardware random number generator to the software-based Yasmarang generator, which was initialized with publicly accessible data like the chip's serial number. This made the seed phrases predictable through offline brute-force attacks, meaning wallets remain at risk until funds are moved to a new wallet generated with the patched firmware. Affected devices include Mk2/Mk3 with firmware 4.0.1–4.1.9 (and up to 5.0.3), Mk4/Mk5 up to version 5.6.0, and Q models up to 1.5.0Q. The only exceptions are seeds created with a high-entropy method like at least 50 independent dice rolls or a strong unique BIP-39 passphrase. All other owners must generate a new seed on the fixed firmware and transfer their assets. A case highlighting the human impact involves a 39-year-old long-term investor who lost 2 BTC (approx. $130,000) in minutes. He had accumulated the Bitcoin over eight years through physical labor, viewing it as a financial lifeline and a retirement plan in a country suffering from hyperinflation. His story underscores that even conservative "buy and hold in cold storage" strategies can be compromised by such underlying technical flaws. From a technical perspective, this incident echoes historical failures where weak random number generators undermined cryptographic security, challenging the assumption that offline storage is automatically foolproof.

cryptonews.ru2 год тому

Bitcoin Withdrawals Continue: 8 Years of Storage in a Coldcard Cold Wallet Ended in Zero

cryptonews.ru2 год тому

Торгівля

Спот
活动图片