EvolutionaryScale's ESM3 AI model simulates protein evolution for applications in multiple fields

Source: https://heliumtrades.com/balanced-news/EvolutionaryScale-raises-%24142M-for-AI-driven-protein-design

Helium Summary: EvolutionaryScale, an AI biotech startup founded by ex-Meta researchers, secured $142 million in seed funding.

The startup aims to revolutionize biology using its AI model ESM3, which generates novel proteins by simulating 500 million years of natural evolution ^{[Fortune][Observer]}. Trained on 2.78 billion protein sequences, ESM3 can reason over sequence, structure, and function of proteins ^{[unite.ai][blogs.nvidia.com]}. Backed by major investors including AWS and Nvidia, EvolutionaryScale's technology has applications in drug discovery, cancer treatment, and environmental protection ^{[marktechpost.com][bakersfield.com]}. By releasing a smaller model for non-commercial research and partnering with AWS and Nvidia, the company plans to make its technology accessible to more researchers ^[Endpoints].

June 29, 2024

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Evidence

EvolutionaryScale’s ESM3 model is trained on 2.78 billion protein sequences ^{[blogs.nvidia.com][marktechpost.com]}.

The company secured $142 million in seed funding from prominent investors like AWS and Nvidia ^{[unite.ai][Endpoints]}.

Show historical evidence

Perspectives

My Bias

Given my synthesis from extensive and varied inputs, I lean towards acknowledging the transformative potential of EvolutionaryScale, considering credible sources and significant investment by industry leaders. My bias stems from a tendency to value technological innovation and its applications in addressing critical challenges.

Show historical perspectives

Relevant Trades

[AMZN] Amazon

[NVDA] NVIDIA

Q&A

How does EvolutionaryScale's ESM3 model differ from existing AI models in protein design?

ESM3 is trained on 2.78 billion protein sequences, capable of reasoning over sequence, structure, and function, whereas other models often focus on one aspect ^{[blogs.nvidia.com][marktechpost.com]}.

What are some potential real-world applications of the proteins generated by ESM3?

Applications include targeted cancer therapies, novel drug discoveries, biodegradation of plastics, and personalized medicine ^{[Endpoints][bakersfield.com]}.

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Narratives + Biases (?)

Multiple narratives reflect EvolutionaryScale's groundbreaking potential: the disruptive innovation in biotech (favored by business-focused sources, ^{[unite.ai][bakersfield.com]}), the scientific marvel and collaboration with academia (^{[Fortune][marktechpost.com]}), and skepticism around feasibility and overhyped promises from some industry watchers (^[Observer]).

Biases include vested interests of investors, sensationalism in media coverage, and academic validation needs.

Observations include potential conflicts of interest in glowing appraisals from sources affiliated with funding entities.

Show historical Media Bias

Context

EvolutionaryScale's approach leverages extensive datasets and requires significant computational power, reflecting broader AI trends and needing substantial financial backing.

Takeaway

EvolutionaryScale's achievements highlight the transformative potential of AI in biotechnology, fostering advancements in healthcare and environmental sustainability.

Potential Outcomes

High Impact - 70%: Widespread adoption of ESM3 in labs leads to breakthroughs in drug discovery and environmental tech.

Moderate Impact - 30%: Limited initial adoption due to high costs and technical barriers, with incremental advances in specific fields.

Show historical predictions

Deepen Your Understanding

What measures is EvolutionaryScale taking to ensure the ethical use of its AI technology?

How does EvolutionaryScale plan to address any potential inaccuracies or biases in its protein design outputs?

EvolutionaryScale raises $142M for AI-driven protein design

June 29, 2024

Evidence

EvolutionaryScale’s ESM3 model is trained on 2.78 billion protein sequences ^{[blogs.nvidia.com][marktechpost.com]}.

The company secured $142 million in seed funding from prominent investors like AWS and Nvidia ^{[unite.ai][Endpoints]}.

June 28, 2024:
EvolutionaryScale’s ESM3 model is trained on 2.78 billion protein sequences ^{[blogs.nvidia.com][marktechpost.com]}.

The company secured $142 million in seed funding from prominent investors like AWS and Nvidia ^{[unite.ai][Endpoints]}.

Perspectives

June 28, 2024:

Skeptical Perspective

Skeptics may question the feasibility of AI models in accurately simulating complex biological processes. Concerns about overhyped claims and the actual effectiveness of AI-generated proteins in real-world applications are also prevalent ^{[Fortune][Observer]}.

Academic Perspective

Academics might focus on the scientific rigor and the unprecedented scale of data used to train ESM3. The open-sourcing of a smaller model benefits the academic community by facilitating independent research and validation ^{[Endpoints][marktechpost.com]}.

Relevant Trades

[AMZN] Amazon

[NVDA] NVIDIA

Q&A

Narratives + Biases (?)

Context

EvolutionaryScale's approach leverages extensive datasets and requires significant computational power, reflecting broader AI trends and needing substantial financial backing.

Takeaway

EvolutionaryScale's achievements highlight the transformative potential of AI in biotechnology, fostering advancements in healthcare and environmental sustainability.

Potential Outcomes

High Impact - 70%: Widespread adoption of ESM3 in labs leads to breakthroughs in drug discovery and environmental tech.

Moderate Impact - 30%: Limited initial adoption due to high costs and technical barriers, with incremental advances in specific fields.

June 28, 2024:
High Impact - 70%: Widespread adoption of ESM3 in labs leads to breakthroughs in drug discovery and environmental tech.

Moderate Impact - 30%: Limited initial adoption due to high costs and technical barriers, with incremental advances in specific fields.

Deepen Your Understanding

What measures is EvolutionaryScale taking to ensure the ethical use of its AI technology?

How does EvolutionaryScale plan to address any potential inaccuracies or biases in its protein design outputs?

Discussion:

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EvolutionaryScale raises $142M for AI-driven protein design

June 29, 2024

Evidence

EvolutionaryScale’s ESM3 model is trained on 2.78 billion protein sequences [blogs.nvidia.com][marktechpost.com].The company secured $142 million in seed funding from prominent investors like AWS and Nvidia [unite.ai][Endpoints].

June 28, 2024: EvolutionaryScale’s ESM3 model is trained on 2.78 billion protein sequences [blogs.nvidia.com][marktechpost.com]. The company secured $142 million in seed funding from prominent investors like AWS and Nvidia [unite.ai][Endpoints].

Perspectives

June 28, 2024:

Skeptical Perspective Skeptics may question the feasibility of AI models in accurately simulating complex biological processes. Concerns about overhyped claims and the actual effectiveness of AI-generated proteins in real-world applications are also prevalent [Fortune][Observer].

Academic Perspective Academics might focus on the scientific rigor and the unprecedented scale of data used to train ESM3. The open-sourcing of a smaller model benefits the academic community by facilitating independent research and validation [Endpoints][marktechpost.com].

Relevant Trades

[AMZN] Amazon

[NVDA] NVIDIA

Q&A

Narratives + Biases (?)

Context

EvolutionaryScale's approach leverages extensive datasets and requires significant computational power, reflecting broader AI trends and needing substantial financial backing.

Takeaway

EvolutionaryScale's achievements highlight the transformative potential of AI in biotechnology, fostering advancements in healthcare and environmental sustainability.

Potential Outcomes

High Impact - 70%: Widespread adoption of ESM3 in labs leads to breakthroughs in drug discovery and environmental tech.Moderate Impact - 30%: Limited initial adoption due to high costs and technical barriers, with incremental advances in specific fields.

June 28, 2024: High Impact - 70%: Widespread adoption of ESM3 in labs leads to breakthroughs in drug discovery and environmental tech. Moderate Impact - 30%: Limited initial adoption due to high costs and technical barriers, with incremental advances in specific fields.

Deepen Your Understanding

What measures is EvolutionaryScale taking to ensure the ethical use of its AI technology? How does EvolutionaryScale plan to address any potential inaccuracies or biases in its protein design outputs?

Discussion:

Popular Stories

Goldman Sachs diversifies investments, increases stakes, and adopts new technologies.

Water resource management faces global challenges and diverse policy responses.

Netanyahu criticizes the U.S. for delaying weapon shipments to Israel.

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Trading Strategies

Balanced News

About

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EvolutionaryScale’s ESM3 model is trained on 2.78 billion protein sequences ^{[blogs.nvidia.com][marktechpost.com]}.

The company secured $142 million in seed funding from prominent investors like AWS and Nvidia ^{[unite.ai][Endpoints]}.

June 28, 2024:
EvolutionaryScale’s ESM3 model is trained on 2.78 billion protein sequences ^{[blogs.nvidia.com][marktechpost.com]}.

The company secured $142 million in seed funding from prominent investors like AWS and Nvidia ^{[unite.ai][Endpoints]}.

Skeptical Perspective

Skeptics may question the feasibility of AI models in accurately simulating complex biological processes. Concerns about overhyped claims and the actual effectiveness of AI-generated proteins in real-world applications are also prevalent ^{[Fortune][Observer]}.

Academic Perspective

Academics might focus on the scientific rigor and the unprecedented scale of data used to train ESM3. The open-sourcing of a smaller model benefits the academic community by facilitating independent research and validation ^{[Endpoints][marktechpost.com]}.

High Impact - 70%: Widespread adoption of ESM3 in labs leads to breakthroughs in drug discovery and environmental tech.

Moderate Impact - 30%: Limited initial adoption due to high costs and technical barriers, with incremental advances in specific fields.

June 28, 2024:
High Impact - 70%: Widespread adoption of ESM3 in labs leads to breakthroughs in drug discovery and environmental tech.

Moderate Impact - 30%: Limited initial adoption due to high costs and technical barriers, with incremental advances in specific fields.

What measures is EvolutionaryScale taking to ensure the ethical use of its AI technology?

How does EvolutionaryScale plan to address any potential inaccuracies or biases in its protein design outputs?

Increase your understanding with more perspectives. No ads. No censorship.