Crypto Flexs
  • DIRECTORY
  • CRYPTO
    • ETHEREUM
    • BITCOIN
    • ALTCOIN
  • BLOCKCHAIN
  • EXCHANGE
  • ADOPTION
  • TRADING
  • HACKING
  • SLOT
  • TRADE
Crypto Flexs
  • DIRECTORY
  • CRYPTO
    • ETHEREUM
    • BITCOIN
    • ALTCOIN
  • BLOCKCHAIN
  • EXCHANGE
  • ADOPTION
  • TRADING
  • HACKING
  • SLOT
  • TRADE
Crypto Flexs
Home»ADOPTION NEWS»Here’s why GPT-4 is ‘dumb’: Untangling the performance hit
ADOPTION NEWS

Here’s why GPT-4 is ‘dumb’: Untangling the performance hit

By Crypto FlexsJanuary 3, 20243 Mins Read
Facebook Twitter Pinterest LinkedIn Tumblr Email
Here’s why GPT-4 is ‘dumb’: Untangling the performance hit
Share
Facebook Twitter LinkedIn Pinterest Email

The areas of artificial intelligence (AI) and machine learning (ML) continue to advance, but they are not without obstacles. A classic example is the performance degradation colloquially referred to as ‘stupidity’ in large language models (LLMs) such as GPT-4. This issue has gained attention in AI discussions, especially since the publication of “Work Pollution: Language Models May No longer be Few-Shot,” which highlights the limitations and challenges currently facing LLM.

Chomba Bupe, a representative figure in the AI ​​community, highlighted X (formerly Twitter) has a major problem. LLMs tend to excel on the tasks and datasets they are trained on, but tend to falter on new, unseen data. The crux of the problem lies in the static nature of post-training in these models. Once the learning phase is complete, performance gradually deteriorates due to limited ability to adapt to new and evolving input distributions.

Source: DALL·E Generation

This performance degradation is of particular concern in areas such as programming, where language models are used and programming language updates occur frequently. Bupe points out that the basic design of the LLM is closer to memorization than understanding, which limits its effectiveness in solving new challenges.

Research conducted by Changmao Li and Jeffrey Flanigan further supports this view. They found that LLMs like GPT-3 outperform on older data sets than on training data. This finding is indicative of a phenomenon called task contamination, where a model’s zero-shot and few-shot features are compromised by limitations in the training data.

Continuous learning, as discussed by Bupe, emerges as a key area of ​​machine intelligence. The challenge is to develop ML models that can adapt to new information without compromising performance on previously learned tasks. this difficulty Contrast this with the adaptability of biological neural networks, which learn and adapt without similar drawbacks.

Alvin De Cruz offers an alternative perspective that suggests that the problem may lie in the evolving expectations of humans rather than in the inherent limitations of the model. But Bupe responds by highlighting the long-standing nature of these challenges in AI, particularly in the area of ​​continuous learning.

In summary, the conversation surrounding LLMs like GPT-4 highlights an important aspect of AI evolution: the essentials of models capable of continuous learning and adaptation. Despite its impressive capabilities, LLMs currently face significant limitations in keeping pace with a rapidly changing world, highlighting the need for more dynamic and evolving AI solutions.

Image source: Shutterstock

Share. Facebook Twitter Pinterest LinkedIn Tumblr Email

Related Posts

Gala Games improves leader board rewards and introduces preference systems.

June 20, 2025

Ether Leeum Whale starts a $ 11 million leverage betting in the 30% increase in ETH prices.

June 12, 2025

AI starts a cost -effective batch API for LLM request.

June 12, 2025
Add A Comment

Comments are closed.

Recent Posts

Safe smart account audit summary

June 27, 2025

CARV’s New Roadmap Signals Next Wave Of Web3 AI

June 27, 2025

CARV’s New Roadmap Signals Next Wave Of Web3 AI

June 27, 2025

Bybit Expands Global Reach With Credit Card Crypto Purchases In 25+ Currencies And Cashback Rewards

June 27, 2025

BYDFi Joins Seoul Meta Week 2025, Advancing Web3 Vision And South Korea Strategy

June 27, 2025

Earns $9,800 Per Day With BTC Breaks Through $107,000, GoldenMining Global Market.

June 27, 2025

Why Bakkt Holdings can buy Bitcoin with a $ 1 billion increase

June 27, 2025

NVIDIA RTX strengthens FITY’s AI -centered innovation in Cooler Design.

June 27, 2025

Join Earn Mining To Mine Easily And Earn $7752 A Day

June 26, 2025

Bitcoin prices return to green -building exercise for more profits

June 26, 2025

Weed® Announces Partnership With Khalifa Kush; Launches Global Commercialization

June 26, 2025

Crypto Flexs is a Professional Cryptocurrency News Platform. Here we will provide you only interesting content, which you will like very much. We’re dedicated to providing you the best of Cryptocurrency. We hope you enjoy our Cryptocurrency News as much as we enjoy offering them to you.

Contact Us : Partner(@)Cryptoflexs.com

Top Insights

Safe smart account audit summary

June 27, 2025

CARV’s New Roadmap Signals Next Wave Of Web3 AI

June 27, 2025

CARV’s New Roadmap Signals Next Wave Of Web3 AI

June 27, 2025
Most Popular

Hodler’s Digest, September 22-28 – Cointelegraph Magazine

September 28, 2024

Amazon shareholders have urged the company to allocate at least 5% of its assets to Bitcoin.

December 9, 2024

Dogecoin now has its own version of Buzzy Bitcoin Ordinals Project Runestone.

April 5, 2024
  • Home
  • About Us
  • Contact Us
  • Disclaimer
  • Privacy Policy
  • Terms and Conditions
© 2025 Crypto Flexs

Type above and press Enter to search. Press Esc to cancel.