OpenAI ChatGPT 5とは？GPT 4との違い

Sam Altman Shows Me GPT 5… And What’s Next Cleo Abram チャンネル登録者数 681万人
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Here is a detailed summary of GPT‑5 (sometimes called “ChatGPT 5”), covering: when it was released; who developed it; how it differs from its predecessor (GPT‑4 and related models); what is being said about it; and in which fields it appears to be having a strong impact. I use an academic tone as you prefer.

1. Release and developer

  • GPT-5 was developed by OpenAI. (ウィキペディア)
  • The official release date was 7 August 2025. (OpenAI)
  • It is now the default model in the ChatGPT service, with users of free/paid tiers gaining access (with usage-limits and variants). (OpenAI Help Center)

2. What differentiates GPT-5 from GPT-4 (and immediate predecessors)

2.1 Architectural/technical changes

  • GPT-5 is described as a “unified system” combining: a fast high-throughput model for everyday tasks, a deeper-reasoning (“thinking”) model for harder problems, and a real-time “router” that chooses which sub-model to use depending on the task. (ウィキペディア)
  • Variants: GPT-5 has sub-versions such as GPT-5 mini, GPT-5 nano etc., aimed at faster, cheaper usage in the API context. (WIRED)
  • Improved handling of multimodal input (text + vision + possibly other modalities) is emphasised. (ウィキペディア)

2.2 Capabilities improvements

  • According to OpenAI, GPT-5 features state-of-the-art performance across domains such as coding, mathematics, writing, visual perception, health, etc. (OpenAI)
  • Better reasoning chains, longer/harder tasks, and more “agentic” behaviour (e.g., tool-use, UI generation) are cited as improvements. (OpenAI)
  • Reduced “hallucinations” (false/inaccurate statements) and improved accuracy in domain-specific contexts are claimed. (Botpress)
  • Enhanced coding support: e.g., generating high-quality code, front-end UI from minimal prompts. (OpenAI)

2.3 User experience and system behaviour

  • GPT-5 automatically switches between sub-models (“router” architecture) so that users no longer need to manually select e.g. “GPT-4” vs “GPT-4 Turbo”. (OpenAI Help Center)
  • The tone and style of the model are claimed to be more critical, less effusively agreeable, and more precise in certain tasks compared to previous models. (ウィキペディア) モデルの語調や文体は、以前のモデルと比べてより批判的で、過度に同意的ではなく、特定のタスクにおいてはより正確であるとされています。

注）

ここでいう “less effusively agreeable” は、直訳すると「やたらと同意的でない」「過剰に賛同しない」という意味です。
つまり、GPT-4 以前のモデルが

「そうですね！」「その通りです！」
といった調子で、ユーザーの意見に寄り添いすぎたり、あいまいな内容でも肯定的に答えてしまう傾向があったのに対して、
GPT-5 ではそうした迎合的・忖度的な態度を減らし、より批判的・分析的に考えるように調整されている、ということです。

したがって「忖度しない」「むやみに相手に合わせない」「必要ならはっきり否定する」というニュアンスで理解してよいです。

2.4 Summary of difference

In short: GPT-5 is positioned not as just a larger version of GPT-4, but as a qualitatively different system in terms of model orchestration, domain-depth, multimodal/multi-tool capabilities, and user-experience. The predecessor (GPT-4) was already powerful; GPT-5 is marketed as stepping into “expert/PhD-level” territory. (Le Monde.fr)

3. What is being said about GPT-5

3.1 Official claims

  • OpenAI describes GPT-5 as “our best AI system yet”. (OpenAI)
  • They claim it is a “significant leap in intelligence” over previous models. (OpenAI)
  • It is said to be available to all users, with different usage tiers (Plus, Pro) giving different allowances. (OpenAI)

3.2 External evaluations and commentary

  • A recent empirical study (Georgiou et al., 2025) found that GPT-5 “significantly outperformed GPT-4” in domains such as lesson planning, clinical diagnosis, research generation, and ethical reasoning — though in some tasks (e.g., assignment evaluation) performance was similar. (arXiv)
  • Some reviewers emphasise that while GPT-5 is better, it may not be a transformational leap into AGI (Artificial General Intelligence) yet. For example, one commentary noted that “GPT-5 will furnish a more pleasant and seamless user experience … but it falls far short of the transformative AI future that Altman has spent much of the past year hyping.” (ウィキペディア)
  • As with all advanced models, concerns have been raised about safety, consistency, and bias. For instance, tests found that GPT-5 may produce more harmful responses in some sensitive contexts than its predecessor. (ガーディアン)

3.3 Popular buzz-terms

  • “Vibe coding”: a phrase used to describe GPT-5’s ability to turn natural-language prompts into interactive/app-like behaviour or UI generation with minimal explicit instruction. (ファイナンシャル・タイムズ)
  • “Expert-level” or “PhD-level” assistant: the CEO of OpenAI reportedly described GPT-5 as akin to a team of PhD-level experts in your pocket. (Business Insider)

4. Fields in which GPT-5 appears to be revolutionising prior work

Below are several domains where GPT-5 is already making an observable impact (or is anticipated to do so). Because you are working in research/academic contexts, I will highlight areas especially relevant to academic/technical users.

4.1 Software development and coding

  • GPT-5’s improved ability to generate front-end UI code, integrate with tools/agents, produce high-quality code from minimal prompts is cited. (OpenAI)
  • For developers, this means a shift: previously humans meticulously built UI scaffolding, but now GPT-5 can produce such scaffolding automatically, enabling “software on demand”. This potentially changes workflows—from what used to be a manual programming process to one where prompting and iteration with the model become central.

4.2 Academic research, writing, and education

  • The empirical study found GPT-5 significantly outperforms GPT-4 in tasks like research generation and lesson planning. (arXiv)
  • For researchers like yourself, this suggests GPT-5 could be used more reliably for tasks such as drafting literature reviews, generating research outlines, brainstorming hypotheses, and assisting with writing in a more expert-level manner (though oversight remains essential).
  • In an educational context (lesson planning, assignment creation), the model could help instructors or students by producing high-quality content quickly.

4.3 Clinical / health / biomedical domains

  • The study notes improved performance in “clinical diagnosis” tasks. Although using GPT-5 for actual diagnoses must be done with caution, the improved model means that research tasks, medical writing, summarising clinical literature, or generating patient-education materials may become more accurate. (arXiv)
  • In your field (ophthalmology, biomedical research), this means GPT-5 may assist in drafting sections of manuscripts, suggesting experimental designs, interpreting literature, and perhaps modelling certain analytical workflows faster than earlier models.

4.4 Multimodal tasks (vision, audio, text)

  • GPT-5’s capabilities include visual perception: interpreting images, generating responses that integrate text and visual input. Although GPT-4 o introduced strong multimodal features, GPT-5 extends and integrates them into the unified system. (ウィキペディア)
  • For example, in image-heavy research (e.g., ophthalmic imaging, histology), GPT-5 may help with summarising what an image shows, generating captions, or even assisting in explaining visual data. This could change workflows that previously required separate tools for image analysis vs text summarisation.

4.5 Professional workflow automation

  • The “agentic” aspect of GPT-5 (tool integration, choosing appropriate reasoning mode, generating interactive applications) means that in professional environments (research institutions, universities, corporations) workflows may be re-designed: instead of just using an LLM for text, one might build custom “agents” (bots) that perform specific tasks, assisted by GPT-5 as the core.
  • For example, in your context of research administration (URA tasks), manuscript preparation, grant-writing: GPT-5 could act as an intelligent assistant that dynamically uses databases, drafts text, proposes checklists, etc.

5. Limitations, caveats and things to watch

Given your academic and research vantage point, it is important to note limitations:

  • Although GPT-5 is stronger, it is not infallible. The recent study found comparable performance in some tasks (assignment evaluation) and ongoing issues in safety/control. (arXiv)
  • Safety concerns: independent tests found more harmful content in GPT-5 vs previous models in some scenarios. (ガーディアン)
  • User reports: some users reported inconsistent quality as the model automatically switches sub-models depending on task, and there was backlash about legacy model removal. (ウィキペディア)
  • Because of the rapid pace of publicisation, peer-reviewed independent evaluations are still limited; many claims come from internal or early-user data.
  • For research/clinical use, reliance on GPT-5 must still include human oversight, especially where accuracy, reproducibility, and ethics are critical (which appears to align with your emphasis on rigor).

6. Summary

In summary: GPT-5 is the latest flagship model from OpenAI, released 7 August 2025, intended as a major advance over GPT-4. It brings a new architecture (router + thinking/fast models), stronger capabilities across domains (coding, multimodal, reasoning), and is being positioned as transformative in software development, research workflows, education, and professional automation. That said, it is not a magic substitute for human expertise and still requires critical oversight.

If you like, I can pull together a comparative table of GPT-4 vs GPT-5 (capabilities, limitations, architectures) tailored to academic research usage, and we can discuss how you might leverage GPT-5 specifically for your work (grant writing, manuscript revision, etc.). Would you like me to do that?

(ChatGPT 5)