GPT-3.5 Turbo
gpt-3-5-turbo-5ec7158b·7 events·first seen 28d agoAliases: GPT-3.5 Turbo, gpt-3.5-turbo, gpt-3.5-turbo-16k, GPT-3.5-turbo
Co-occurring entities
More like this (12)
Recent events (7)
GPT-3.5 Turbo fine-tuning and API updates
OpenAI has opened fine-tuning access for GPT-3.5 Turbo, allowing developers to customize the model with their own data for specific use cases. This extends fine-tuning capabilities previously available on older GPT-3 models to the more capable Turbo variant. The announcement also includes associated API updates to support this functionality.
Introducing ChatGPT and Whisper APIs
OpenAI announced the release of dedicated APIs for ChatGPT (gpt-3.5-turbo) and Whisper, enabling developers to integrate conversational AI and speech-to-text capabilities into their applications. The ChatGPT API offered significant cost reductions compared to existing GPT-3.5 endpoints. This marked a major step in OpenAI's platform strategy, opening programmatic access to its most widely used consumer models.
OpenAI Announces Function Calling, Longer Context, and API Price Reductions
OpenAI introduced function calling capabilities to its API, enabling models to reliably output structured JSON for calling developer-defined functions. The update also includes longer context windows, more steerable models (gpt-3.5-turbo-16k and gpt-4 updates), and reduced pricing on several API tiers. These changes significantly expand the practical utility of OpenAI models for agentic and tool-use applications.
GPT-4 API General Availability and Completions API Deprecation Plan
OpenAI has announced general availability of the GPT-4 API, alongside GPT-3.5 Turbo, DALL·E, and Whisper APIs. Concurrently, OpenAI is releasing a deprecation plan for older models in the Completions API, which are set to retire at the beginning of 2024. This marks a significant milestone in OpenAI's API product lifecycle, transitioning GPT-4 from limited access to broad developer availability.
Structural role injection via Handlebars triple-brace interpolation in LLM prompts: empirical analysis across delimiter families and models
A new arXiv paper demonstrates that Handlebars templating's HTML auto-escaping—the default in Microsoft Semantic Kernel—provides uneven protection against structural role injection attacks, where attacker-controlled data carries chat role delimiters to forge higher-privilege turns. The authors conduct 5,760 trials across seven delimiter families, two attack objectives, and four models (GPT-3.5 Turbo, GPT-4o mini, GPT-4.1 mini, Claude Haiku 4.5), finding that HTML escaping neutralizes angle-bracket-based delimiters (ChatML, Llama-3, XML) but leaves colon- and Markdown-based families fully exposed. GPT-3.5 Turbo follows task-hijack instructions in 97% of raw and 91% of escaped trials; Claude Haiku 4.5 resists both objectives almost entirely. The paper concludes that HTML escaping cannot substitute for structural separation of instruction and data.
GPT-4o mini: advancing cost-efficient intelligence
OpenAI announced GPT-4o mini, a smaller and more cost-efficient version of GPT-4o, targeting applications that require lower latency and reduced inference costs. The model is positioned to outperform competing small models on key benchmarks while maintaining multimodal capabilities. It replaces GPT-3.5 Turbo as OpenAI's recommended entry-level model for cost-sensitive deployments.
Fine-tuned PEGASUS-large outperforms LLaMA-3 and GPT-3.5 for automatic research paper title generation
Researchers propose a system for generating research paper titles from abstracts using pre-trained and large language models, evaluated on CSPubSum, LREC-COLING-2024, and a new dataset SpringerSSAT. Fine-tuned PEGASUS-large outperforms fine-tuned LLaMA-3-8B and zero-shot GPT-3.5-turbo across most metrics including ROUGE, METEOR, BERTScore, and SciBERTScore. The work is a narrow NLP application study with limited broader implications for the AI/ML landscape.