Interactive Improvements in CommunicationImproved interaction between ChatGPT and humans can lead to better overall outcomes. Here are some examples of how you can enhance the communication process: 1.Iterative question-answering: Refine y…

What is "prompt engineering"? Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skill…

How we should evaluate technical capability in M&A from PE perspective? Is there enough room to improve? How was the price? Over-pricing or underestimated? We reviewed three acquistion targets, Seagate-Hard drive manufacturers, McAfee, and…

The ChatGPT era has revolutionized artificial intelligence and language processing, but with these advancements comes a new set of challenges. One of the most pressing concerns is the future shortage of training data. In this article, we'l…

www.youtube.com Formula Problem statement If from <input> we could know <output>, then <someone> could derive a benefit by Inputs(X) What are the inputs X? What does X fail to encode? What problems might this create? Outputs(Y) How is Y constructed? - Automation </someone></output>…

A framework for understanding sources of harm throughout the Machine Learning Life Cycle As I introduced several times, I am really interested in data quality and its impact on AI. www.youtube.com Academic article: A Framework for Understa…

AI would be a true threat to humans? If you are familiar with sci-fi, AI is a definitely threatening technology that potentially destroys human beings as Skynet in Terminator 2 did. But will it really happen? waitbutwhy.com The point is th…

This course is to learn potential AI roles from various perspectives without any technical deep-dive. The goal of this course is to help you become an architect to draw a blue print. Not a builder. The failure of AI comes from typically ar…

Question Answering Tasks in Machine Learning Question answering is one of the major problem sets in NLP, in a nut shell, this is simpler Reading Comprehension problem in GMAT or other types. There are multiple types of questions and texts,…

What is overfitting? Overfitting occurs when the model has a high variance, i.e., the model performs well on the training data but does not perform accurately in the evaluation set. What is Overfitting in Deep Learning [+10 Ways to Avoid I…

Clustering 101 Clustering is the most typical machine learning of unsupervised learning. It means we don't have training data or correct label, but machine learning automatically put labels, or grouping datasets. In today's article, I will…

Fixed income markets: Issuers: entities that create fixed-income securities in order to raise funds (e.g.,governments, corporations, commercial banks, states, municipalities) Intermediaries: entities that assist issuers in creating and sel…

NLP = playing with unstructured string data String data is super messy. Before running ML or advanced analytics, we need to cleanse data. Encoding is another tricky issue in text data analysis. Remember, Emoji. We need to understand ASCII …

The confusion matrix is super confusing. https://www.researchgate.net/figure/Confusion-matrix-and-performance-equations-The-confusion-matrix-included-four_fig1_340034692 Everytime I forget the definition of TP, FP, etc, and metrics as well…

www.economist.com 今年の1月15日は、とあるウェブサイトの20歳の誕生日だった。 Wikipediaは、35歳の私が大学生のころ、レポートを書くとき、格好のコピペ元だった。大学の教員もそんなサボりが起こることは心得ていて、Wikiのコピペは大幅減点だったのだが…

AIに人間の仕事が代替されると言われて結構時間が経っていることに気づいた。 多分初めの方にそれが述べられていたのは、下記の野村総研のレポート。 https://www.nri.com/-/media/Corporate/jp/Files/PDF/news/newsrelease/cc/2015/151202_1.pdf ここでは、…

The Actual Difference Between Statistics and Machine Learning Mediumの古いネタを引っ張り出してきた。 英語読める人は、本文を見てほしい。 “The major difference between machine learning and statistics is their purpose. Machine learning models…

あんまり普段仕事の話を書かないのですが、お仕事ではもっぱらGoogle Cloudをいじり倒しています。 ちょっと前までは、割とウェブログ系のデータをいじいじとしながら、時系列予測や、ありがちなCV期待値みたいなものをScikit-learnとかKerasでグリグリモデ…

友達がシェアしてたのを見て、ちょっと思うところがあり、こっそり書いてみた。3月の記事だから結構今更だろうか。 今データサイエンティストを目指してる人の7割が5年後に年収350万にしかなれない - データエンジニアの日記上記記事の論旨を説明すると、今…

Mckinseyから下記リンクのレポートが出た。 How artificial intelligence can deliver real value to companies | McKinseyリンク先のレポートもなかなか読み応えがあって面白いので、是非読んでほしい。業界別にAIの投資や将来機会、レベル格付け等を行って…