Mecletter February ｜ AWS Hero Tells You About 2024 AI Technology Trends and Success Strategies!🤖
Date of Creation : 2024-02-28
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Thanks to your support, Meckletter has been revamped.
From now on, we will deliver IT trends packed with expert insights in an easy-to-understand and readable manner.
Today’s keyword that will enhance our tech capabilities is #AI.
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AI Trends and Successful Adoption Strategies for 2024 as Explained by an AWS Hero
Discussions about AI are never-ending. If AI were a movie, it would have already dominated the box office. From super-large AI to generative AI and AI semiconductors… the new technologies emerging every year remind us of exciting spin-off films.
The growth trend in the AI market is also remarkable. It is expected to grow by 36.8% annually over the next five years, reaching a market size of 1,000 trillion by 2030. While AI is driving innovation across various industries, not all companies have successfully adapted to this trend. Implementing AI is a challenging task for any industry or company.
As we enter the era of AI, we asked an AWS hero about the latest trends and successful strategies for companies wondering what strategies they should establish and how other companies are doing.
Are You Part of the 40%?🤖
According to a survey by ITWorld/CIO, the AI adoption rate among domestic companies in 2023 is 40%. Currently, 23.8% of companies are actively using AI in their operations, and 17.3% are conducting pilot projects for adoption. Compared to last year’s IBM report of 22% in the ‘2022 AI Adoption Index’, this represents about a twofold increase in just one year.
You may have heard that global big tech companies have conducted mass layoffs to increase AI investments; in January alone, over 34,000 jobs were cut. This indicates a strong commitment from companies to enhance operational efficiency through AI adoption. This has significant implications for the domestic market, suggesting that more and more companies, both enterprises and startups, will prepare for AI adoption.
**Is the Success Rate Fifty-Fifty?**😯
In fact, at Megazone Cloud, the number of AI-related consultation requests has significantly increased since June of last year. In particular, the increase in generative AI – LLM (Large Language Model) field is impressive, with high demand in industries such as finance, insurance, manufacturing, and e-commerce, where there is a lot of documentation. Looking more closely, there is a trend of adopting product sales/safety stock forecasting through Amazon Forecast, personalized recommendation systems via Amazon Personalize, and consumer analysis and visualization using Amazon Comprehend and Amazon Quicksight.
Currently, most generative AI projects are in the PoC (Proof of Concept) and demo stages, and the establishment of practical production environments is expected in the middle to latter half of this year. However, not all companies that have conducted PoCs succeed in their AI/ML projects.
What is Holding Back AI Adoption?💦
Continue Reading the Full Article
RAG, Overcoming the Limitations of Generative AI!
The AI trend to watch in 2024 is still ‘Generative AI’. In particular, since the launch of ChatGPT last November, there has been remarkable progress in the LLM (Large Language Model) field. LLMs have learned vast amounts of data, acquiring human-level language understanding and text generation capabilities.
However, concerns are still high. This is because LLMs can generate content that is not factual or lacks evidence. This issue, known as Hallucination, poses a significant obstacle to commercializing generative AI. The accuracy of information is incredibly important in business.
RAG Comes to the Rescue of LLMs😇
There is an important technology to overcome these limitations. That is RAG (Retrieval Augmented Generation). By utilizing search engines to verify the factuality of the text generated by LLMs and generating text based on verified information, accuracy is greatly enhanced.
RAG Technology You Need to Know Right Now💻
To help you understand RAG, I would like to explain two commonly used technologies: Embedding Model and Vector Database. The Embedding Model is a technology that converts data such as words, sentences, images, and graphs into vectors.
Continue Reading the Full Article
🌎Go Global🌎
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