The document discusses generative artificial intelligence (AI) and its challenges and implications, moderated by Carlos J. Costa from ISEG. It covers various models and applications, including ChatGPT and Google Bard, as well as the broader generative AI ecosystem, highlighting tools and services available. Key challenges and sectors impacted by generative AI are also identified, including education, research, and healthcare.

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Carlos J. Costa (ISEG)
GENERATIVE AI: CHALLENGES
AND IMPLICATIONS
Moderator: Prof. Carlos J. Costa, ISEG

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Carlos J. Costa (ISEG)
Index
• Presentation of the moderator
• Generative AI
• LLM
• ChatGPT
• Bard
• Generative AI Ecosystem
• Challenges and Implications

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Carlos J. Costa (ISEG)
Carlos J. Costa
Associate Professor with Habilitation
• Chat-GPT Task Force @ ISEG
• Costa, C. (2023 Jan. 6) “GPT-3 e a utilização de Inteligencia Artificial no Ensino”.
isegtech.blogs.sapo. https://isegtech.blogs.sapo.pt/gpt-3-e-a-utilizacao-de-ia-no-
ensino-7355
• Costa, C. (2023 Jul. 16) “Bard: Finalmente em Portugal”. isegtech.blogs.sapo.
https://isegtech.blogs.sapo.pt/bard-finalmente-em-portugal-8321

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Carlos J. Costa (ISEG)
Generative AI
• Generative artificial intelligenceincludes
models that can generate new content,
such as images, music, and text.
• An example of these models is ChatGPT.

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Carlos J. Costa (ISEG)
LLM
• A large language model (LLM) is a type of
language model characterized by its ability
to achieve general-purpose language
processing and generation.

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Carlos J. Costa (ISEG)
ChatGPT
• Conversational generative artificial
intelligence chatbot
• LLM-based chatbot
• developed by OpenAI
• Launched on November 30, 2022,
• Generative, Pre-Trained, Transformer
Name
Release
date Developer Number of parameters Corpus size
Training cost
(petaFLOP-day) License
GPT-2 2019 OpenAI 1.5 billion
40GB[103] (~10 billion
tokens) MIT
GPT-3 2020 OpenAI 175 billion 300 billion tokens 3640proprietary
GPT-4 March 2023 OpenAI Exact number unknow Unknown proprietary

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Carlos J. Costa (ISEG)
Google Bard
• Conversational generative artificial
intelligence chatbot
• Developed by Google,
• Based initially on the LaMDA family of
large language models (LLMs) and later
the PaLM LLM.
Name Release date Developer
Number of
parameters Corpus size
Training cost
(petaFLOP-day) License
BERT 2018 Google 340 million 3.3 billion words 9Apache 2.0
XLNet 2019 Google ~340 million 33 billion words Apache 2.0
GLaM (Generalist Language Model) December 2021 Google 1.2 trillion 1.6 trillion tokens 5600proprietary
Minerva June 2022 Google 540 billion 38.5B tokens from webpages proprietary
LaMDA (Language Models for Dialog Applications) January 2022 Google 137 billion 1.56T words, 168 billion tokens 4110proprietary
PaLM (Pathways Language Model) April 2022 Google 540 billion 768 billion tokens 29250proprietary
PaLM 2 (Pathways Language Model 2) May 2023 Google 340 billion 3.6 trillion tokens 85000proprietary

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Carlos J. Costa (ISEG)
Generative AI Ecosystem

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Carlos J. Costa (ISEG)
Generative AI Ecosystem
Other services:
• Chat PDF https://www.chatpdf.com/
• ChatGPT https://chat.openai.com/
• Chatsonic https://app.writesonic.com/
• Consensus https://consensus.app/
• Elicit https://elicit.org/
• Google Bard https://bard.google.com/
• Microsoft Bing Chat (no Edge) https://www.bing.com/
• Research Rabit https://www.researchrabbit.ai/
• SciCite https://scite.ai/
• SciSpace https://typeset.io/
• SciStyle https://www.scistyle.com/
• You.com https://you.com/

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Carlos J. Costa (ISEG)
Generative AI Ecosystem
• GPT4ALL
(https://gpt4all.io) allows to
run locally many pretrained
models

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Carlos J. Costa (ISEG)
Generative AI Ecosystem
• FreedomGPT
(https://www.freedomgpt.com)
• 100% uncensored and private AI chatbot.
• ALPACA and LLAMA models

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Carlos J. Costa (ISEG)
Challenges and Implications
• Education
• Research
• Software development
• Creative industries
• Manufacturing
• Cybersecurity
• Client Support
• Health care