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
Uneak White's Personal Brand Exploration Presentation
Generative AI: Redefining Creativity and Transforming Corporate Landscape
1. Generative AI: Redefining Creativity and
Transforming Corporate Landscape
Minoru “Mick” Etoh, Ph.D.
Professor, Osaka University
9/19/2023
@mickbean
https://www.linkedin.com/in/micketoh/
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2. it's crucial to cultivate a
culture of using
technology effectively
• Divide between AI adopters
and non-adopters
• Technology is not a
substitute for social and
political change but rather a
complement to it.
2
3. Zhao, Wayne Xin, et al. "A survey of large language models." arXiv preprint arXiv:2303.18223 (2023).
Generative AI: A New Era in Education and
Corporate World
3
4. Time
Performance ASR
2012 2014 2016
DNN
Image
Recognition
CNN
Machine
Translation
LSTM-
Attention
GAN
Transformer
2018
LLM
Pre-Training
2020 2022
Reinforcement
Learning
from Human Feedback
(RLHF)
4
Diffusion
Models
6. OPEX: $255M
CAPEX: $400M?
Development Cost
Last year's loss: $540 M in 2022
Operating Cost
Running Cost: $700,000/Day
$0.01/response
Duration: instructGPT 3 years
Source: https://www.businessinsider.com/openai-2022-
losses-hit-540-million-as-chatgpt-costs-soared-2023-5
https://growjo.com/company/OpenAI
Microsoft
Generative
AI per se
Direct via Web
Microsoft
SaaS
License
Enterprise
DX
$88.7M per year.(2022)
655 Employee
total funding
$11B
LLM
Development
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There are probably fewer than 50 people in Japan who can design an LLM from scratch.
7. Two interpretations offered by LLMs
A machine that
generates the most
plausible texts in
response to directives.
A multi-lingual
knowledge base that
provides answers to
inquiries. 7
9. Impact on
Industries:
• Advancing digital transformation within
enterprises.
• Profound R&D impacts, especially in drug
discovery and healthcare.
• In Japan, a significant boost to creativity.
11. Value creation is several trillion dollars
annually.
• Approximately 75% of the value
brought by use cases of creative AI
is concentrated in four areas:
customer operations, marketing and
sales, software engineering, and
R&D.
• For instance, tasks include
supporting interactions with
customers, generating creative
content for marketing and sales,
and creating computer code
based on natural language prompts.
• Impacts industries such as banking,
high-tech, and life sciences.
11
12. 1
2
Drastic Change of Enterprise SaaS
Front office Back office
Automation of Communication & Workflow
13. 14
Moor, Michael, et al. "Foundation models for generalist medical artificial intelligence." Nature 616.7956 (2023): 259-265.
19. Proposal for Proper Use of Image Generative AI
and Proper Application of the Copyright Law
1.For image-generative AI like Stable Diffusion, bypassing
Article 30-4 of Copyright Law isn't allowed; prior written
consent from copyright holders is a must.
2.License fees for AI's use of copyrighted images should be
based on consumer usage frequency.
3.Only AI-generated works with clear human creative input
receive copyright protection; purely AI creations don't.
Source https://support-creators.com/archives/87
20. Article 30-4 of Copyright Law Act (2019)
Source. https://japannews.yomiuri.co.jp/society/general-news/20230429-106420/
French expert couldn’t understand why Japanese law “gave such preferential treatment to AI development.”
24. 1. Telemarketers
2. English Language and Literature Teachers, Postsecondary
3. Foreign Language and Literature Teachers, Postsecondary
4. History Teachers, Postsecondary
5. Law Teachers, Postsecondary
6. Philosophy and Religion Teachers,
7. Sociology Teachers, Postsecondary
8. Political Science Teachers, Postsecondary
9. Criminal Justice and Law Enforcement Teachers, Postsecondary
10.Sociologists
Source: Occupational Heterogeneity in Exposure to Generative AI By Ed Felten
(Princeton), Manav Raj (University of Pennsylvania), Robert Seamans (New York
University), 19 Apr 2023
Occupations most exposed by generative AI
25
26. Reading, Writing, Listening, and Speaking.
Extinction of the
business model:
professor who
individually
instructs students
in basic actions.
27
27. Draft Guidelines for the Use of Generative AI in Schools by
the Ministry of Education, Culture, Sports, Science and
Technology of Japan (July 2023)
1. Generative AI offers significant convenience but also presents risks such as
copyright infringement, spreading misinformation, and influencing creativity.
2. Initial use in schools should be limited and carefully managed.
3. Misconduct includes using AI-generated content as
students' work for submissions or competitions.
4. Appropriate use includes employing AI to find missing perspectives and deepen
discussions during thinking and planning activities.
5. Children might use generative AI outside school, hence the necessity for
enhancing the development of their information utilization skills to combat the risk
of misinformation and 'filter bubbles'.
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28. Non-Routine Tasks
Routine Tasks
Knowledge Work
Manual Labor
Zone2︓ AI enhancement Zone1: AI/Robotics
Enhancement
Zone 4: AI/Robotics Replacement
Sports referee
Supermarket cashier
Zone 3: AI replacement
Agricultural produce sorter
Actor/Actress
Dentist
Radiologist
Insurance Claims Examiner
Real estate broker
Firefighter
Tax Preparer
Judicial scrivener Construction equipment operator
Manager
Economist
Caregiver
Psychiatrist
Lawyer
Factory assembler
Retail clerk
Dancer
Technological Dichotomy: Augmentation or Threat?
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29. Non-Routine Tasks
Routine Tasks
Knowledge Work
Manual Labor
Zone2︓ AI enhancement Zone1: AI/Robotics
Enhancement
Zone 4: AI/Robotics Replacement
Sports referee
Supermarket cashier
Zone 3: AI replacement
Agricultural produce sorter
Actor/Actress
Dentist
Radiologist
Insurance Claims Examiner
Real estate broker
Firefighter
Tax Preparer
Judicial scrivener Construction equipment operator
Manager
Economist
Caregiver
Psychiatrist
Layer
Factory assembler
Retail clerk
Dancer
Technological Dichotomy: Augmentation or Threat?
30
AI automation frontline
31. Not AGI but Somewhat Singularity
Machine
Mixed
Zone
Human
Non-routine tasks
Routine tasks
The left behind
humanity
Domination
32
32. Control Protocols of Generative AI Entities
Computer Science
Transparency, Data Integrity, & Security
of Generative AI Implementation
Ethics
Law,
Guideline,
Design
Endless Dialogue
Norms
Religion
Social structure
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33. Future Outlook: Generative AI‘s Direction
Scaling law: Performance monotonically increases with
increased computational complexity, data size, and parameters.
Integration of multimodal information (audio, video, IoT data).
Emergence of open-source, open-data, and lightweight
computing models.
Transition from inductive tasks to deductive tasks (multi-step
reasoning)
Automatic acquisition of knowledge through embodiment and
agency.
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36. Californian School Girl Version
So like, what's gonna be expected from people in the next five
years?
It's gonna be super important to know how to use generative AI as
a tool, you know? And also, we're gonna need to figure out if we
should use stuff made by these AIs or not.
That's why schools are gonna change too.
Instead of trying to figure out if a student actually did their
homework or not, it's gonna be more about if they can write
something even better than a computer can.
Because of the whole AI thing, the stuff that only humans can do is
gonna become even more important, and it's gonna change how
businesses and schools work and stuff. 37
37. British Professor Version
As we contemplate the ensuing five years, what shall be demanded
of mankind? A crucial competency shall be the effective utilization of
generative AI as an instrument, in addition to the discernment
required for determining the adoption or rejection of works produced
by such AI.
Thus, the domain of education shall undergo transformation. Rather
than ascertaining the veracity of whether a student has completed
their homework autonomously, the emphasis shall shift towards
assessing the individual’s capacity to compose textual content
exceeding the capabilities of their personal computing devices.
Owing to the disruptive force exerted by generative AI, the value that
solely humans can provide will be honed, ultimately altering the
modus operandi of both corporate administration and education. 38