#large-language-models

#large-language-models

Delve, intricate, surpass. Perhaps you've been hearing and seeing these words more often -- ChatGPT may be to blame. People are adopting language from the chatbot's lexicon, according to Florida State University researchers . The university's Modern Languages and Linguistics, Computer Science, and Mathematics departments collaborated to reveal that the chatbot's most overused words are influencing human speech patterns.

"When we train our model, we're not training it to be an amazing conversationalist with you," Frosst said. "We're not training it to keep you interested and keep you engaged and occupied. We don't have like engagement metrics or things like that." The Canadian AI startup was founded in 2019 and focuses on building for other businesses, not for consumers. It competes with other foundational model providers such as OpenAI, Anthropic, and Mistral and counts Dell, SAP, and Salesforce among customers.

A phrase I've often clung to regarding artificial intelligence is one that is also cloaked in a bit of techno-mystery. And I bet you've heard it as part of the lexicon of technology and imagination: "emergent abilities." It's common to hear that large language models (LLMs) have these curious "emergent" behaviors that are often coupled with linguistic partners like scaling and complexity. And yes, I'm guilty too.

Not long ago, a storefront sign was the most important marketing channel a retailer had. If you didn't have one, customers didn't know you existed. Today, for mortgage companies, that sign has been replaced by something else entirely: search. But with borrowers now turning to ChatGPT and other AI tools instead of Google, even ranking on the first page may not mean you'll be found.

Last week, Google AI pioneer Jad Tarifi sparked controversy when he told Business Insider that it no longer makes sense to get a medical degree - since, in his telling, artificial intelligence will render such an education obsolete by the time you're a practicing doctor. Companies have long touted the tech as a way to free up the time of overworked doctors and even aid them in specialized skills, including scanning medical imagery for tumors. Hospitals have already been rolling out AI tech to help with administrative work.

AI chatbots are widespread in many different sectors as they can provide natural and engaging interactions. We already know these models aren't good at protecting information.

LM Caches play a critical role in improving the efficiency and scalability of deploying large language models by caching and reusing previously computed results.

"The firm, based in San Francisco, California, detailed the system in a blog post and a technical description on 5 August. On some tasks, gpt-oss performs almost as well as the firm's most advanced models."

The environmental audit by Mistral reveals that the majority of CO2 emissions and water consumption arise during model training and inference, not from construction or end-user equipment.

The rise of agentic AI - autonomous systems that understand, plan, and act using large language models (LLMs) - is rapidly reshaping how developers and data professionals think about automation.

"RNGD provides a compelling combination of benefits: excellent real-world performance, a dramatic reduction in our total cost of ownership, and a surprisingly straightforward integration."

Despite impressive capabilities, large language models have yet to produce a genuine breakthrough. They lack fundamental aspects of human thought, remaining static and unable to learn from experience.

We show that LLMs - Gemma 3, GPT4o and o1-preview - exhibit a pronounced choice-supportive bias that reinforces and boosts their estimate of confidence in their answer, resulting in a marked resistance to change their mind.

Retrieval Augmented Generation (RAG) combines the power of Large Language Models (LLMs) with a custom knowledge base, enabling precise and contextually relevant responses from customers.

The Model Context Protocol (MCP) is an open standard that enables large language models to interact with external tools and data through a standardized interface.

The research shows that large language models consistently advise women to ask for lower salaries than men, despite identical qualifications. For instance, a difference in advice led to a gap of $120K a year between genders in some fields.

"Nvidia's multi-million-token context window is an impressive engineering milestone, but for most companies, it's a solution in search of a problem," said Wyatt Mayham, CEO and cofounder at Northwest AI Consulting. "Yes, it tackles a real limitation in existing models like long-context reasoning and quadratic scaling, but there's a gap between what's technically possible and what's actually useful."

If AI suggests unregistered or inactive domains, threat actors can register those domains and set up phishing sites. As long as users trust AI-provided links, attackers gain a powerful vector to harvest credentials or distribute malware at scale.

Rising demand among marketers for AI search expertise drives agencies to create specialist units to assist clients in understanding technology's impact on consumer habits.

Fine-tuning large language models requires huge GPU memory, leading to challenges in acquiring larger models, but QDyLoRA addresses this by enabling dynamic low-rank adaptation.

Without understanding AI tools’ inner workings, you risk frustration and subpar results. Mastering foundational principles transforms your collaboration with this technology.