Generative AI: Redefining Creativity and Transforming Corporate Landscape
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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
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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/ 1
- 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 6 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
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- 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.
- 10. Copyright © 2023 SambaNova Systems Confidential & Proprietary | Internal Use Only Pace of Commerce will Increase by 10x AI will touch every function of every company in every industry Agent Console IVR Research Databases Trading Systems eDiscovery Case Mgmt Campaign Tools Web CMS CMS Articles Document Repository Document Management Codebases DevOps Contact Center Finance Legal Marketing Media Document Processing Software Development Enterprise Grade Foundation Model 10 10
- 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.
- 14. Copyright © 2023 SambaNova Systems Confidential & Proprietary | Internal Use Only Regression Decision Tree MACHINE LEARNING Past Present BERT UNET DEEP LEARNING Diffusion GPT GENERATIVE AI Future Domain-trained models A few very large models PERVASIVE AI Purpose-built. Private. Packaged. Private data adapted models Open source models AI is a journey: Invest in a foundation for the future 15
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- 18. Shadow of Stable Diffusion Source: https://www.upworthy.com/lensa-app-ai-profiles-privacy-ethics
- 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.”
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- 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
- 25. natural sciences and engineering social sciences and humanities AI and Ethical Challenges: Education and Beyond 26
- 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'. 28
- 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? 29
- 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
- 30. AI adopters and non-adopters 31
- 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 33
- 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. 34
- 34. https://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html Present Future Trajectory based on the past growth rate Trajectory based on the present growth rate Trajectory based on the future exponential growth rate Time Performance How to predict the future 35
- 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