ChatGPT用户现在可以免费使用Dall-E 3创建图像

币界网2024-08-11 tarihinde yayınlandı2024-08-11 tarihinde güncellendi

币界网报道:

OpenAI引入了一项新功能,允许免费版ChatGPT的用户每天使用Dall-E 3创建最多两张图像,Dall-E是该公司最强大的将文本转换为图片的AI模型。

OpenAI在X(前身为推特)上宣布,该功能以前是ChatGPT高级用户的保留,现在将向全球约1.9亿月活跃用户开放。

Dall-E 3因“画质不佳”而受到批评

该初创公司写道:“我们很高兴为ChatGPT Free用户介绍使用Dall·E 3每天最多创建两个图像的功能。”。

人们可以使用该功能创建图像,如个性化卡片或演示文稿的视觉效果。OpenAI提供了免费ChatGPT用户可以用来探索该工具的提示示例,如下图所示。

Dall-E 3

除了生成图像外,新功能还将帮助用户改进提示,以提高准确性,特别是与逼真图像相关的提示。尽管OpenAI已经开放了对该功能的访问,但那些想不受限制地使用它的人仍然需要为无限使用付费。

Dall-E3于2023年9月发布,是OpenAI最先进的文本到图像生成AI模型。它可以创造一系列的视觉风格,包括异想天开的插图和超现实的图像。虽然Dall-E 3的使用量有所增加,但人们对其可靠性表示担忧。

今年2月,一位名为“Pbadolvini”的X用户说:“最初,Dall-E 3制作了令人惊叹的高质量图像,但最近,输出往往不尽如人意,有时甚至达到了我所说的‘灾难性’质量水平。这尤其发生在我在短时间内提出了许多请求之后,或者当我试图生成同一主题的变体时。”

目前尚不清楚OpenAI是否解决了向免费层ChatGPT用户推出之前提出的问题。

İlgili Okumalar

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

This article explains the three primary methods for Codex to interact with a computer, each with distinct use cases, permission boundaries, and trust levels. **1. Computer Use:** This offers the broadest access, allowing Codex to visually control and interact with the graphical user interface of authorized macOS/Windows apps, system settings, and even iOS simulators. It's ideal for tasks lacking APIs or structured tools, such as operating legacy software or multi-app workflows. However, it's the slowest method and has the widest permission scope, requiring careful supervision for sensitive actions. **2. Chrome Extension:** This grants Codex access to the user's logged-in Chrome browser state, including cookies, profiles, and open tabs. It's best for tasks requiring user identity across websites like Gmail, LinkedIn, Salesforce, or internal dashboards. Its key advantage is multi-tab control for complex workflows. While more powerful for browser-based tasks than Computer Use, it carries higher sensitivity as actions are performed under the user's identity. **3. In-App Browser:** This is a browser isolated within the Codex thread, separate from the user's personal browsing data. It excels in web development and debugging scenarios—previewing local servers, testing responsive layouts, or annotating designs directly on the page. Its isolation is a strength for development but a limitation for tasks requiring login sessions. The core principle is to choose the narrowest, safest, and most structured interface for the task. Use plugins or MCPs first, resort to visual control (Computer Use) only for GUI-dependent tasks, employ the Chrome extension for identity-reliant browser work, and prefer the In-App Browser for isolated development. **Appshots** are clarified as a fourth, complementary tool for *inputting* context—capturing a screenshot of a window to point Codex to something—rather than a method for Codex to *act*. Together, this layered approach highlights a key to AI agent productization: not granting unlimited permissions, but constraining them within clear boundaries for specific tasks while preserving user oversight.

marsbit1 saat önce

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

marsbit1 saat önce

The "Iron Rule" of Chip Equipment Is Being Broken

For years, the semiconductor equipment industry followed an unwritten "iron rule": suppliers offered steep discounts for new tool introductions (Design-in) and faced consistent price pressure during repeat orders, especially during market downturns. This long-standing buyer's market dynamic is now being upended. Recently, SK Hynix's primary equipment suppliers have reportedly requested a 3-4% price *increase*, a nearly unprecedented move. This shift is driven by a severe supply-demand imbalance fueled by the AI compute boom. Securing equipment has become an urgent arms race as chipmakers' expansion speed dictates their ability to fulfill massive AI chip orders. Key areas feeling the strain include: **TCB (Thermal Compression Bonding) Equipment:** Demand is exploding, driven by the simultaneous needs of HBM4 memory stacking, AI chip Chip-on-Substrate (C2S), and logic Chiplet Chip-on-Wafer (C2W) packaging. Players like Hanmi Semiconductor, Hanwha Semitech, and ASMPT are receiving major orders. While hybrid bonding is seen as the future, TCB remains the pragmatic choice for HBM4 mass production, with its lifecycle extended by relaxed specifications and ongoing technological upgrades. **Test Equipment Bottlenecks:** Ironically, AI-driven shortages are now crippling test equipment manufacturing. Critical components like FPGAs, Driver ICs, and CPUs face severe shortages and extended lead times (up to 52 weeks for FPGAs), as AI data center and server vendors prioritize supply. This creates a paradoxical cycle: AI chip shortages drive fab expansion, which requires more test equipment, whose production is delayed because its key parts are diverted to make AI chips. The industry is entering a broad, AI-powered upcycle. SEMI forecasts global semiconductor equipment sales to hit a record $156 billion by 2027, fueled by investment in advanced logic/foundry, HBM-driven DRAM, and advanced packaging (like CoWoS). Major players like TSMC, SK Hynix, and Micron are aggressively ramping capital expenditure. In conclusion, leading equipment vendors are no longer just selling tools; they are selling the critical capability to deliver AI-era capacity. Pricing power is shifting decisively to those with indispensable technology in key process nodes like advanced logic, HBM, and advanced packaging, rewriting the industry's traditional power structure.

marsbit1 saat önce

The "Iron Rule" of Chip Equipment Is Being Broken

marsbit1 saat önce

İşlemler

Spot
Futures
活动图片