События и конференции
Анонсы и материалы про мероприятия отрасли.
Материалы на русском языке; развёрнутая версия содержит полный текст, ссылка на страницу издания — внизу карточки.
Анонсы и материалы про мероприятия отрасли.
Материалы на русском языке; развёрнутая версия содержит полный текст, ссылка на страницу издания — внизу карточки.
Джесен Хуан говорит о своем новом инвестиционном проекте.
Florida today became the first U.S. state to sue OpenAI Group PBC and its chief executive, alleging that its product ChatGPT can be harmful to its users and that the company has failed to make clear these dangers to the public. “Today, we announced the first-in-the-nation state-led lawsuit against OpenAI and its CEO, Sam Altman,” […] The post Florida AG sues OpenAI and Sam Altman over claims the technology is dangerous and exploits its users appeared first on SiliconANGLE.
Во втором квартале Hewlett Packard Enterprise Co. продала искусственные интеллектуальные серверы в огромных количествах, что помогло компании превзойти ожидания по прибыли и выручке. В результате, акции компании подскочили во время расширения торгов. За квартал HPE сообщила прибыль до определенных расходов, таких как компенсация акций, в 79 центов за акцию, что превысило ожидания на…
Intel Corp. today debuted a line of central processing units based on its latest manufacturing process and shared new details about its next-generation graphics cards. Both product families are geared toward artificial intelligence data centers. Intel is also prioritizing the AI infrastructure market with a new series of Ethernet chips that it announced in conjunction. […] The post Intel introduces Xeon 6+ server processors, previews upcoming graphics cards appeared first on SiliconANGLE.
16% of my monthly Pro+ allowance. Gone. For basically nothing
TeamPCP? Or copycat malware dev?
Hacking voting machines is so 2017. Phishing, impersonation pose the real election risks
First it tops OpenAI's valuation, then it beats Altman to the IPO punch
But opposition continues to mount
Plant will consist of modular, self-contained generator units
Activist behind PG&E Hinkley lawsuit turns her ire towards data centers
Facility was being used for illegal streaming
Необходимо дополнительное 250 ГВт мощности в случае "агрессивного, но все еще вероятного" сценария.
Поддержка Китая относительно выручки от отрасли полупроводников больше.
Big news in enterprise AI broke over the weekend as Chinese AI startup MiniMax released its highly anticipated M3 large language model on Sunday evening Eastern time, pairing frontier-tier coding and agentic performance with a 1-million-token context window and native multimodality for a fraction of the cost of leading proprietary models, with pricing starting at just $20 per month under its new subscription token plans. The company's leadership also announced plans to deliver the model under an open source license including "open weights," allowing for full enterprise downloading and customizability free-of-charge, coming sometime in the next 10 days. For now, it is available via the MiniMax API at a special discounted price of $0.3 per 1 million input tokens and $1.20 per million output tokens (on fresh cache) for the next week — beating proprietary U.S. giants like Google, OpenAI and Anthropic handily on cost, while also eclipsing the performance of the latest models from the former two on selected benchmarks.Even at its full price of $0.6/$2.40 per million input/output tokens, MiniMax-M3 remains at just 8-20% the cost of the leading, proprietary U.S. models. The traditional matrix governing large language model development has long dictated a rigid choice: software developers can either access top-tier closed-source intelligence behind restrictive APIs, or deploy nimble, cost-effective open models that falter on multi-step reasoning, dense coding tasks, and massive data sequences. MiniMax-M3 fundamentally upends this paradigm. By unifying these two historically separated frontier capabilities, M3 introduces a level of comprehensive utility previously restricted to expensive, closed-source ecosystems, effectively shifting the baseline of open-weights systems while drastically minimizing the operational compute footprint required to execute complex development loops. VentureBeat Frontier AI Model API Pricing SnapshotModelInputOutputTotal CostSourceMiMo-V2.5 Flash$0.10$0.30$0.40Xiaomi MiModeepseek-v4-flash$0.14$0.28$0.42DeepSeekdeepseek-v4-pro$0.435$0.87$1.305DeepSeekMiniMax-M3$0.30$1.20$1.50 (limited time only)MiniMaxGemini 3.1 Flash-Lite$0.25$1.50$1.75GoogleMiMo-V2.5$0.40$2.00$2.40Xiaomi MiMoGrok 4.3 low context$1.25$2.50$3.75xAIGLM-5$1.00$3.20$4.20Z.aiKimi-K2.6$0.95$4.00$4.95Moonshot/KimiGLM-5.1$1.40$4.40$5.80Z.aiGrok 4.3 high context$2.50$5.00$7.50xAIQwen3.7-Max$2.50$7.50$10.00Alibaba CloudGemini 3.5 Flash$1.50$9.00$10.50GoogleGemini 3.1 Pro Preview ≤200K$2.00$12.00$14.00GoogleGPT-5.4$2.50$15.00$17.50OpenAIGemini 3.1 Pro Preview >200K$4.00$18.00$22.00GoogleClaude Opus 4.8$5.00$25.00$30.00AnthropicGPT-5.5$5.00$30.00$35.00OpenAINew MiniMax Sparse Attention (MSA) technique helps keep the model's cost lowAt the core of the model's efficiency lies an architectural departure from classic Transformer networks. Standard attention mechanisms scale quadratically ($O(N^2)$), meaning computational and financial costs explode as text inputs lengthen. To combat this "inherent flaw," the engineering team implements MiniMax Sparse Attention (MSA), a clean, extensible sparse attention blueprint. To visualize this innovation, think of traditional full attention as an editor reading an entire library from scratch every time they need to verify a single sentence. MSA acts as an intelligent indexing clerk, using a pre-filtering phase to partition Key-Value (KV) matrices into highly precise blocks. At the operator level, MSA uses a "KV outer gather Q" approach. The system treats KV blocks as an outer loop, dynamically aggregating only the specific queries that hit them. Because each data block is read exactly once and memory access remains strictly contiguous, hardware utilization skyrockets. In internal trials, MSA runs more than 4x faster than alternative open-source solutions like Flash-Sparse-Attention or flash-moba. When managing a maxed-out context length of 1 million tokens, M3’s per-token compute demand drops to just 1/20th of the prev
Oracle and AWS add eight more locations to multi-cloud offering
Также будет служить партнером по электронной коммерции для футбольных групп.
Получите полное контроль над своими данными и устраните риски крупномасштабных утечек данных.
Платформа компании использует лазеры для осмотра полупроводников без повреждения их
Across the frontier labs, the highest prompt injection figures published this spring are Anthropic’s. Point a red-teamer at its newest model in a browser, and the attacker hijacked it 31.5% of the time before safeguards engaged. OpenAI, Google, and Meta never gave security leaders a comparable number to set beside it. That figure looks like a liability. In this comparison, it is the opposite. It's the one solid piece of ground.Four frontier labs each shipped a prompt injection disclosure, and no two match. Anthropic put 244 pages and four agentic surfaces on the table on May 28. OpenAI reported one surface, connectors. Google moved the subject out of the model card and into a separate safety framework. Meta shipped no closed-model card at all. The Cross-Vendor Prompt Injection Disclosure Grid below maps what each lab tested, what each one measured, and the four places a side-by-side comparison falls apart.A prompt injection hides a malicious instruction in something an agent reads, a web page, a document, or a tool result. One planted line can exfiltrate records or fire off actions nobody approved, and these cards are a buyer's only first-party evidence.There is no industry standard for measuring any of this, and that is the root of the problem. Carter Rees, VP of AI at Reputation, told VentureBeat that prompt injection breaks the assumption that every legacy tool was built on. "A phrase as innocuous as, 'ignore previous instructions' can carry a payload as devastating as a buffer overflow, yet it shares no commonality with known malware signatures." With no shared signature to scan for, each lab built its own yardstick, and the results do not line up. Adam Meyers, Senior Vice President of Counter Adversary Operations at CrowdStrike, said that the exposure is now the buyer's to manage. "As you implement AI, it increases your attack surface, so now you have to be able to protect those AI models against adversary misuse or data poisoning or prompt injection." CrowdStrike's own frontline data shows the threat side is not standing still. In its 2026 Financial Services Threat Landscape Report, released in May, the company reported adversaries using AI to compress the time from initial access to impact faster than legacy defenses can respond.Anthropic measured four surfaces. The numbers swing by an order of magnitude depending on which one you read.The Opus 4.8 card does what others do not: It breaks prompt injection out by surface, and the spread is the story.Put the model in a coding environment, and an adaptive attacker from Gray Swan's Shade tool got through on 7.03% of single attempts with thinking on. Safeguards pulled that to 2.09%.Move the same class of attack into a browser, the surface behind Claude in Chrome and Claude Cowork, and the floor gives way. Anthropic put professional red-teamers on 129 web environments held out from training and printed every result in Table 5.2.2.4.A on page 81 of the system card. Per-attempt is the share of all injection attempts that got through across 129 environments at 10 tries each. Per-scenario is the harder cut, the share of environments where at least one try landed. Read down the per-attempt column without safeguards, thinking on, and the raw rate drops with each generation, from Sonnet 4.6 at 50.7% to Opus 4.8 at 31.5%. The lowest in the table, 5.9%, belongs to Mythos Preview, which nobody can buy yet. Turn safeguards on, and Opus 4.8 drops to 0.5%. Turn thinking off and it drops to zero across all 129 environments. OpenAI measured one surface, with attacks it already knew.The GPT-5.5 card, published April 23 and updated April 24, handles prompt injection in one place, a single section on robustness to known attacks against connectors. OpenAI reports it as a robustness score where higher is better, the inverse of an attack success rate. GPT-5.5 came in at 0.963, down from 0.998 for GPT-5.4-thinking. That one figure is the whole disclosure.Anthropic tested four surfaces against an ad
Kai is an extension for RAD Studio (Delphi and C++ Builder) that integrates with external AI providers
Штат Бакингтон обнаружил, что неудачно вступил в число миллиардеров
Что исправит агентивная ИИ
How institutions are balancing AI growth, budget pressure, and infrastructure modernization
База данных, содержащая 64,000 записей пользователей, была опубликована на GitHub после того, как атакующий заявил о взломе всех систем Atlas.
Company partners to build facility at new Frier Vest industrial park
Один из нескольких проектов, которые компания планирует в стране.
Фондовый рынок оценивает компанию в $570 миллионов.
Последние изменения в законодательстве направлены на уменьшение беспокойства по поводу приватности, но остается широкий сомнительный взгляд на возможность их реализации.
Company looks to replace existing warehouse development
Will cover the full electrical path of the data center
Will support power delivery to the 300MW campus
System relies on a proprietary storage layer as AWS moves to separate storage and compute to fit mega AI demands
Delivered by Dell Technologies
Company set to pivot Christina Lake campus towards AI and HPC hosting
Rapid7: Атакующие используют уязвимость обхода аутентификации в реальном мире, что означает необходимость экстренного обновления для пользователей PAN-OS.
Forget Wintel, we're living in a Winvidia world now
Engineers' weekends ruined as Dashlane's automatic protections kicked in
Proposed legislation threatens fines and prison for reckless damage. Russian Prez must be shaking in his boots
The man behind Redmond's direct billing model and its geo rollout explains why the new version forgets the channel to its cost