【講演】デジタルヘルスシンポジウム @京大 12/4/2015 「IoT時代のクラウドとAIの展望
This talk covers these three topics:
1. Current Market Trend of Mobile IoT Health Care Devices and their business models
2. Is mobile cloud is applicable for medical services?
3. Future vision of machine translation and data mining technologies for Clinicaland Pharmaceutical field
米国を中心とした 人工知能(AI)の事業トレンドを紹介する.“AI”というと私がリードしたドコモの 「しゃべって コンシェル」やApple Siri ,Amazon Echo, Microsoft Cortanaなどの擬人化エージェント,あるいはロボットを想起することが多いが,米国ではより一般的にAIは農業や交通,流通など各産業における自動化,効率化技術のマーケティング用語として用いられる場合が多い.実質はデータに基づく機械学習を用いた最適化である.基盤となる実装アルゴリズムの多くは急速にコモンディティ化して行く.画像解析,パーソナル化,音声対話,マーケティングオートメーションの多くは商用化段階にありレッドオーシャン化が進みつつある.農業,教育,医療,法律,福祉,防災などこれまでIT化が進んでいなかった領域での動きを含めてAIの事業化動向を解説する.
【講演】デジタルヘルスシンポジウム @京大 12/4/2015 「IoT時代のクラウドとAIの展望
This talk covers these three topics:
1. Current Market Trend of Mobile IoT Health Care Devices and their business models
2. Is mobile cloud is applicable for medical services?
3. Future vision of machine translation and data mining technologies for Clinicaland Pharmaceutical field
米国を中心とした 人工知能(AI)の事業トレンドを紹介する.“AI”というと私がリードしたドコモの 「しゃべって コンシェル」やApple Siri ,Amazon Echo, Microsoft Cortanaなどの擬人化エージェント,あるいはロボットを想起することが多いが,米国ではより一般的にAIは農業や交通,流通など各産業における自動化,効率化技術のマーケティング用語として用いられる場合が多い.実質はデータに基づく機械学習を用いた最適化である.基盤となる実装アルゴリズムの多くは急速にコモンディティ化して行く.画像解析,パーソナル化,音声対話,マーケティングオートメーションの多くは商用化段階にありレッドオーシャン化が進みつつある.農業,教育,医療,法律,福祉,防災などこれまでIT化が進んでいなかった領域での動きを含めてAIの事業化動向を解説する.
IBM Watsonに代表されるAI技術の台頭、LINEの普及によるチャットでの顧客対応など、もう電話、メールだけの時代は終わりました。
電話、メール、チャット、スマホアプリ…今後も増え続ける新しいチャネルの対応に、すべて人間で対応していきますか?
簡単な問い合わせは機械が対応する時代がもう来ています。
本日は次世代の自動応答サービスをご紹介します。
「IoT(Internet of Things)の時代」伊万里Porto3316オープン記念セミナ 160917知礼 八子
2016年9月17日、佐賀県伊万里市のコワーキング/イベントスペースにて行われた第1回地方版ドローンサミットにて急遽場を繋ぐために「IoT(Internet of Things)の時代」と題して講演させて頂いた際のプレゼン資料。
引用・参照時には出典元として「株式会社ウフル 八子の資料より」などを明記してください。
Generative AI: Redefining Creativity and Transforming Corporate LandscapeOsaka University
The advent of Generative AI is redefining the boundaries of creativity and markedly transforming the corporate landscape. One of the pioneering technologies in this domain is the Reinforcement Learning from Human Feedback (RLHF). Combined with advancements in LLM (Language Model) has emerged as a notable player. LLM offers two primary interpretations: firstly, as a machine capable of generating highly plausible texts in response to specific directives, and secondly, as a multi-lingual knowledge repository that responds to diverse inquiries.
The ramifications of these technologies are widespread, with profound impacts on various industries. They are catalyzing digital transformation within enterprises, driving significant advancements in research and development, especially within the realms of drug discovery and healthcare. In countries like Japan, Generative AI is heralded for its potential to bolster creativity. The value generated by such AI-driven innovations is estimated to be several trillion dollars annually. Intriguingly, about 75% of this value, steered by creative AI applications, is predominantly concentrated within customer operations, marketing and sales, software engineering, and R&D. These applications are pivotal in enhancing customer interactions, generating innovative content for marketing campaigns, and even crafting computer code from natural language prompts. The ripple effect of these innovations is palpable in sectors like banking, high-tech, and life sciences.
However, as with every innovation, there are certain setbacks. For instance, the traditional business model of individualized instruction, as seen in the context of professors teaching basic actions, is on the brink of obsolescence.
Looking ahead, the next five years pose pertinent questions about humanity's role amidst this technological evolution. A salient skillset will encompass the adept utilization of generative AI, paired with the discernment to accept or critique AI-generated outputs. Education, as we know it, will be reimagined. The evaluative focus will transition from verifying a student's independent work to gauging their ability to produce content surpassing their AI tools. Generative AI's disruptive nature will compel us to re-evaluate human value, reshaping the paradigms of corporate management and educational methodologies
To be or not to be an academic, big enterprise, startup job that is the qu...Osaka University
"Who said it first is not important." Who gets there first is."
(Takeo Kanade, Circa 1990s)
Before joining a Big Enterprise, Check these
Empathy with the company's vision and mission.
Senior management prepares their own presentation materials (with high IT literacy).
There are executives who joined the company mid-career from outside.
There is a good employee training program.
There are many retired employees who are active after leaving the company.
There is an organization that integrates marketing, development, and operations.
There are no academic cliques.
日本ではディープテック・スタートアップが育つ環境がない。1. イノベーター人材育成が不十分、2.ベンチャーキャピタル側の人材欠如、3. 大企業側レセプターが未発達という課題を指摘した上で、今後どうすれば良いのかという未来志向の議論をしたい。巷間で言われる「AIは幻想だった」という評価を乗り越えるべく「AIはデジタルだ」の見地から、米国の非営利団体OpenAIが開発した巨大言語モデルGPT-3を例にして、これから見えるイノベーショントレンドを共有する。
Business Environment of Deep Tech AI Startups
There is no naturing environment for deep-tech startups to grow in Japan. I would like to point out the following issues: (1) insufficient development of innovator education system, (2) lack of human resources on the venture capital side, and (3) lack of development of receptors on the large enterprises side. In order to overcome the reputation of "AI was an illusion." from the viewpoint of "AI is digital.", we will share the innovation trends to be seen using the huge language model GPT -3 developed by the non-profit organization OpenAI in the United States as an example.
The most conservative part in a company is mediocre experts who love status quo. Top tier experts tend to climb up mountains from one peak to another peak, so as to explore new ideas and products. You must move also from one to another one. It is said,
“You can raise the bar or you can wait for others to raise it, but it’s getting raised regardless.” Raise your bar higher enough no to succeed now but in the future eventually. Your life is counted hoe many oh-shit moment you experienced. Gotta run.