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Microsoft’s agreement with two founders of Inflection is the latest sign that deep-pocketed companies are scooping up much of the expertise in AI

A IA não é boa nem má, mas vai inaugurar uma era global de complexidade e ambiguidade.

BearManBull Escreveu:O url está mal!

É uma nova geração de chips de inteligência artificial, que vai "impulsionar uma nova revolução industrial". É assim que a Nvidia - a nova "two trillion dollar baby" - descreve o seu novo semi-condutor.

O ânimo quanto à IA viu um novo impulso esta segunda-feira, após a Bloomberg reportar que a Apple e a Google estão em conversações para a instalação do modelo de IA generativa da Google, o Gemini, nos telemóveis da empresa da maça.

Apesar de as empresas não terem confirmado qualquer tipo de conversações neste sentido, as ações estão já a reagir: a Alphabet sobe 6,65% para 151,62 dólares e a Apple ganha 2,17% para 176,36 dólares.

Também a Nvidia, fabricante de semicondutores usados nos modelos de IA, está a valorizar, registando ganhos de 4,65% para 919,21 dólares.

A empresa de Tim Cook estará à procura de um parceiro que possa instalar inteligência artificial no sistema operativo dos seus aparelhos eletrónicos de forma a potenciar o seu uso e oferecer novas funcionalidades.

Trabalhadores que não acompanhem a mudança correm o risco de ficar para trás, avisa o CEO da Siemens Portugal. “Os robôs não nos vão substituir a todos, pelo menos nas tarefas críticas”, mas o emprego vai mudar.

A adoção da Gen AI irá redefinir a dinâmica competitiva no setor financeiro, podendo capacitar novos participantes no mercado ou alterar a influência relativa das instituições existentes. E dada a rapidez com que está a evoluir, é provável que, durante este ano, a Gen AI passe a integrar gradualmente a generalidade das operações das instituições financeiras e empresas de retalho em todo o mundo.

Elon said we should announce an initial $1B funding commitment to OpenAI. In total, the non-profit has raised less than $45M from Elon and more than $90M from other donors.

We all understood we were going to need a lot more capital to succeed at our mission—billions of dollars per year, which was far more than any of us, especially Elon, thought we’d be able to raise as the non-profit.

As we discussed a for-profit structure in order to further the mission, Elon wanted us to merge with Tesla or he wanted full control. Elon left OpenAI, saying there needed to be a relevant competitor to Google/DeepMind and that he was going to do it himself. He said he’d be supportive of us finding our own path.

Elon soon chose to leave OpenAI, saying that our probability of success was 0, and that he planned to build an AGI competitor within Tesla.

We're sad that it's come to this with someone whom we’ve deeply admired—someone who inspired us to aim higher, then told us we would fail, started a competitor, and then sued us when we started making meaningful progress towards OpenAI’s mission without him.
We are focused on advancing our mission and have a long way to go. As we continue to make our tools better and better, we are excited to deploy these systems so they empower every individual.

Researchers typically seek interpretable and high-performing models. Making the best model, however, usually increases model complexity, which tends to reduce interpretability. Understanding the tradeoff between accuracy and interpretability becomes critical for successful analytics as more corporations turn to AI models to spur development. The connection between accuracy and interpretability will be covered in this subsection.

some interpretability may be sacrificed in order to get the most accurate model possible

The explanation is needed in order to acquire information, create a trustworthy connection between humans and AI systems, improve and learn from the system, as well as to comply with regulation.

The demand for Trustworthy AI will expand as the technology is used more often in practical applications, particularly when making automated decisions that might have adverse effects on human lives.

Elon Musk claims OpenAI is using GPT-4 to ‘maximize profits’ instead of ‘for the benefit of humanity.’

Machine learning algorithms outcomes are more understandable and transparent by XAI techniques, e.g., LIME (local interpretable model-agnostic explanations) (Mathews, 2019), RETAIN (reversed time attention) (Choi et al., 2016), and LRP (layer-wise relevance propagation) (Binder et al., 2016). LIME is a post hoc model in prediction accuracy techniques, which operates as a technique providing explanations and transparency after the decision-making process. A notable advantage of LIME is its model-agnostic nature, enabling its application across various model types. The methodology of LIME entails perturbing or subtly modifying the model's inputs to examine the resulting changes in outputs. This facilitates the identification of inputs that exert the most influence on the outputs, thereby offering valuable insights into the model's decision- making process (Mathews, 2019). RETAIN is an XAI technique focused on healthcare applications to provide transparency, e.g., in heart failure diagnosis (Moreno-Sanchez, 2020).

"The single greatest contribution we have made to
society is that we finally made it possible so that all of our children don't have to learn C++"

The computer should do what you intended it to do.

Thanks to artificial intelligence and the groundbreaking work of our industry, we have closed the technology divide dramatically. Now, everyone is a programmer, and the programming language of the future is called "human."

- Jensen Huang

MarcoAntonio Escreveu:Boa partilha, perneta. Esta questão tem que ver com algo que já referi aqui por algumas vezes no tópico, o famigerado "problema da black box". Dois artigos introdutórios sobre o tema:

Explainability in Deep Learning: Demystifying the Black Box

Peeking Inside the Black Box: An Introduction to Explainable AI

eXplainable AI (XAI) methods for improving trust in AI models has arisen. XAI has become a popular research subject within the AI field in recent years.

The primary goal of XAI is to obtain human-interpretable models, especially for applications in sensitive sectors such as military, banking, and healthcare applications, since domain specialists need help solving problems more effectively, but they also want to be provided with meaningful output to understand and trust those solutions.

A gigante tecnológica estabeleceu uma "parceria estratégica" com a startup Mistral, rival francesa da OpenAI - que tem sido a principal aliada da Microsoft no que toca à inteligência artificial.

Algumas gigantes tecnológicas como a Microsoft, a Intel, a Samsung e a Nvidia vão investir na "startup" Figure AI, que está a desenvolver robôs na forma de humanos. A empresa está em vias de captar cerca de 675 milhões de dólares.