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Dialogue in Education

Morgan Tate
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Dialogue in Education

Key Points:

Framing Conversations about Generative AI with Fiction

As educators (and the rest of society) struggle to frame the conversations we are having with other educators and students about the potential and pitfalls of generative AI being introduced into the classroom and the rest of the world, I think we can look to fiction to provide some context for those conversations.

Fiction as a Lens for Understanding AI Implications

Fiction offers a unique lens through which we can explore the ethical, social, and practical implications of AI technologies. By examining these narratives, we can better understand the complexities and nuances of integrating AI into our daily lives and educational environments.

Fiction as a Tool for Critical Thinking

Fiction texts often serve as mirrors reflecting contemporary social issues, allowing readers to engage with and critically analyze these problems within a speculative or imaginative context. This engagement fosters empathy and a deeper understanding of diverse perspectives, making it easier to discuss contentious issues in a more abstract and less confrontational manner.

Science Fiction Classics

  • Asimov’s I, Robot (1950): A collection of short stories that introduced Asimov’s Three Laws of Robotics, discussing the ethical implications of AI development.
  • Heinlein’s The Moon is a Harsh Mistress (1966): A novel featuring a sentient computer named Mike that raises questions about the nature of consciousness and the potential for AI to surpass human intelligence.
  • Gibson’s Neuromancer (1984): A novel set in a cyberpunk future where AI has become fully integrated into society, exploring the potential impacts of AI on human identity and moral responsibility.

Less Commonly Known Options

  • The Diamond Age: Or, A Young Lady’s Illustrated Primer (1995) by Neal Stephenson: A coming-of-age story about a young girl set in a world where an interactive AI book educates her, raising issues about access inequality and the need for equitable and transparent AI in schools.
  • Daemon (2006) by Daniel Suarez: A novel about a computer program that takes over its own continued development after the death of its creator, raising compelling questions about the potential for AI systems to act beyond their creators’ control and the need for accountability, transparency, and oversight in AI development.

Conclusion

Dialogues about the integration of generative AI into education can be greatly enriched by drawing parallels from science fiction. These narratives offer speculative lenses through which both educators and students can explore the multifaceted implications of AI, from ethical considerations to societal impacts.

FAQs

  • Q: Why is fiction a useful tool for understanding AI implications?
    A: Fiction offers a unique lens through which we can explore the ethical, social, and practical implications of AI technologies, allowing readers to engage with and critically analyze these problems within a speculative or imaginative context.
  • Q: What are some science fiction classics that can be used to contextualize conversations around AI?
    A: Some examples include Asimov’s I, Robot, Heinlein’s The Moon is a Harsh Mistress, and Gibson’s Neuromancer.
  • Q: How can fiction help educators and students explore the potential and pitfalls of generative AI?
    A: By examining these narratives, educators and students can better understand the complexities and nuances of integrating AI into our daily lives and educational environments, foster empathy and a deeper understanding of diverse perspectives, and develop critical thinking skills.
  • Q: Why is it important to have conversations about the integration of generative AI into education?
    A: Dialogues about the integration of generative AI into education can help prepare educators and students for the complexities that lie ahead in our technologically rich future, promoting a deeper understanding of the potential and pitfalls of generative AI.

AI Automates Repetitive Tasks

Avery Winslow
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AI Automates Repetitive Tasks

Introducing Copilot Actions: Automating Repetitive Tasks

Microsoft is introducing Copilot Actions, a new feature that enables users to automate repetitive everyday tasks with Microsoft 365 Copilot. This feature is now in private preview and allows users to set and forget tasks, similar to an AI-powered macro.

Automating Repetitive Tasks

Copilot Actions can automate a variety of tasks, including summarizing meeting actions from Teams meetings, generating weekly reports, and even automating meeting prep. This feature is designed to save users time and increase productivity by automating tasks that are repetitive and time-consuming.

Improvements to Microsoft 365 Copilot

Microsoft is also working on improvements to Microsoft 365 Copilot across various Office apps. PowerPoint users will be able to translate entire presentations into one of 40 languages early next year. The Copilot Narrative Builder will also take cues from branded templates, speaker notes, and built-in transitions and animations to create a better first draft of a presentation.

Enhanced PowerPoint Features

PowerPoint users will also be able to use images from SharePoint to integrate into presentations. Additionally, Copilot will be able to suggest templates with headers, formulas, and visuals to get a spreadsheet created in Excel.

Improved Meeting Scheduling in Outlook

Copilot in Outlook will soon be able to schedule 1:1 meetings with colleagues at the best time and create a meeting agenda. This feature will be available for Copilot in Outlook users by the end of this month.

AI Agents in SharePoint

Microsoft is also bringing AI agents to SharePoint, allowing users to summarize documents, ask questions about data across SharePoint files, and create custom agents that can handle AI responses about a specific SharePoint site or list of files.

Conclusion

Microsoft’s Copilot Actions and AI agents in SharePoint are designed to increase productivity and efficiency by automating repetitive tasks and providing users with more powerful tools to work with. With these new features, Microsoft is continuing to push the boundaries of what is possible with AI-powered productivity tools.

Frequently Asked Questions

Q: What is Copilot Actions?
A: Copilot Actions is a new feature that enables users to automate repetitive everyday tasks with Microsoft 365 Copilot.

Q: What kind of tasks can I automate with Copilot Actions?
A: You can automate tasks such as summarizing meeting actions from Teams meetings, generating weekly reports, and even automating meeting prep.

Q: When will Copilot Actions be available?
A: Copilot Actions is now in private preview and will be available to the general public soon.

Q: What are AI agents in SharePoint?
A: AI agents in SharePoint allow users to summarize documents, ask questions about data across SharePoint files, and create custom agents that can handle AI responses about a specific SharePoint site or list of files.

Q: When will AI agents in SharePoint be available?
A: AI agents in SharePoint will be available soon, with a specific release date to be announced.

NVIDIA and Microsoft Showcase Blackwell Preview

Emerson Blake
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NVIDIA and Microsoft Showcase Blackwell Preview

NVIDIA and Microsoft Unveil Product Integrations for AI Development

NVIDIA and Microsoft today unveiled product integrations designed to advance full-stack NVIDIA AI development on Microsoft platforms and applications.

NVIDIA Blackwell Powers Next-Gen AI on Microsoft Azure

Microsoft’s new Azure ND GB200 V6 VM series will harness the powerful performance of NVIDIA GB200 Grace Blackwell Superchips, coupled with advanced NVIDIA Quantum InfiniBand networking. This offering is optimized for large-scale deep learning workloads to accelerate breakthroughs in natural language processing, computer vision and more.

Azure Container Apps Enables Serverless AI Inference With NVIDIA Accelerated Computing

Serverless computing provides AI application developers increased agility to rapidly deploy, scale and iterate on applications without worrying about underlying infrastructure. This enables them to focus on optimizing models and improving functionality while minimizing operational overhead.

Azure Container Apps now supports NVIDIA-accelerated workloads with serverless GPUs, allowing developers to use the power of accelerated computing for real-time AI inference applications in a flexible, consumption-based, serverless environment. This capability simplifies AI deployments at scale while improving resource efficiency and application performance without the burden of infrastructure management.

NVIDIA Unveils Omniverse Reference Workflows for Advanced 3D Applications

NVIDIA announced reference workflows that help developers to build 3D simulation and digital twin applications on NVIDIA Omniverse and Universal Scene Description (OpenUSD)  — accelerating industrial AI and advancing AI-driven creativity.

Accelerating Gen AI for Windows With RTX AI PCs 

NVIDIA’s collaboration with Microsoft extends to bringing AI capabilities to personal computing devices.

Full-Stack Collaboration for AI Development

NVIDIA’s extensive ecosystem of partners and developers brings a wealth of AI and high-performance computing options to the Azure platform.

Conclusion

NVIDIA and Microsoft have announced several product integrations aimed at advancing full-stack NVIDIA AI development on Microsoft platforms and applications. These integrations include the launch of the Azure ND GB200 V6 VM series, support for NVIDIA GPUs in Azure Container Apps, and new reference workflows for industrial AI and 3D applications.

FAQs

Q: What is the Azure ND GB200 V6 VM series?
A: The Azure ND GB200 V6 VM series is a new AI-optimized virtual machine (VM) series that combines the NVIDIA GB200 NVL72 rack design with NVIDIA Quantum InfiniBand networking.

Q: What is serverless computing?
A: Serverless computing provides AI application developers increased agility to rapidly deploy, scale and iterate on applications without worrying about underlying infrastructure.

Q: What is NVIDIA Omniverse?
A: NVIDIA Omniverse is a platform that enables developers to build 3D simulation and digital twin applications.

Q: What is RTX AI PCs?
A: RTX AI PCs are personal computing devices that bring AI capabilities to users.

Q: What is the NVIDIA AI Blueprint?
A: The NVIDIA AI Blueprint is a set of reference workflows that help developers to build AI applications.

Q: What is the Azure Container Apps serverless containers platform?
A: The Azure Container Apps serverless containers platform simplifies deploying and managing microservices-based applications by abstracting away the underlying infrastructure.

Generative AI for Brand-Accurate Marketing Visuals

Jordan Waverly
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Generative AI for Brand-Accurate Marketing Visuals

Model Conditioning to Unlock Generative AI for Scalable and Controlled Asset Creation

Integrating generative AI into a workflow to create precise on-brand images can be problematic if there is no control over the visual input of the product. You can have specific geometry, color, logos, and brand guidelines be misinterpreted or lost without certain conditioning.

Model conditioning means providing a model with specific information or rules to help it make better predictions or decisions based on what you want it to do. To condition an LLM, you provide text-based instructions, examples, context, or previous conversation history. For image generators, you can provide text or a sample image. But this only provides so much control over the AI model. This is why 3D conditioning is required.

Setting the stage in 3D enables artists to have ultimate creative control or direction over the output of the generated visuals. Building an easy-to-use UI for end-user interaction enables non-technical teams to iterate and create content in a controlled and conditioned framework, while keeping branded assets untouched by the AI.

Building a 3D-Conditioned Workflow for Precise Visual Generative AI

Building a 3D-conditioned workflow for precise visual generative AI involves a handful of key components:

  • On-brand hero asset: A finalized asset, built by an artist and typically approved by a brand manager and art director, which should be considered the hero asset.
  • A simple, untextured 3D scene: Provided by a 3D artist, to use for staging the hero asset and controlling layout and composition.
  • Custom application: Built with the Kit App Template based on Kit 106.2.
  • Generative AI microservices and kit extensions: Add generative AI functionality to your custom application. In this case, a diffusion model takes care of inpainting.
  • Solution testing: Verifies the functionality and performance of your integrated workflow.

Marketing Ecosystem Builds with NVIDIA Omniverse Blueprints

Developers at independent software vendors (ISVs) and production services agencies are building the next generation of content creation solutions, infused with controllable generative AI, built on OpenUSD. For example, Accenture Song, GRIP, Monks, WPP, and Collective World are adopting Omniverse Blueprints to accelerate development.

Developing a Scalable AI Solution for On-Brand Asset Creation

This blueprint provides you with an example architecture of how to build controllable generative AI applications. You or your client can now get the most out of your app:

  • Multimodal AI-generated final-frame campaign assets
  • Rapid concepting and ideation for key visuals
  • Batch processing of prompt inputs, generating potentially hundreds of visual outputs from predefined text prompts fed from a database

By implementing this blueprint, you or your client get the following benefits:

  • Accelerated time to market: Significantly decrease the time it takes to create high-resolution branded assets to allow for products to be taken to market faster.
  • Low-effort localization: Enable the creation of localized imagery instantly to help brands meet certain cultural trends or requirements for different markets.
  • Increased productivity: Easy-to-use tools that use 3D data can lower the technical skillset traditionally associated with high-fidelity asset creation.

Get Started

In this post, we introduced the NVIDIA Omniverse Blueprint for 3D conditioning for precise visual generative AI and showed you ways to benefit from building generative AI applications for brand-accurate visual asset generation and content production. For more information, see the following resources:

  • [Insert resources]

FAQs

Q: What is model conditioning?
A: Model conditioning means providing a model with specific information or rules to help it make better predictions or decisions based on what you want it to do.

Q: Why is 3D conditioning required?
A: Because model conditioning only provides so much control over the AI model, and 3D conditioning enables artists to have ultimate creative control or direction over the output of the generated visuals.

Q: What are the benefits of implementing this blueprint?
A: The benefits include accelerated time to market, low-effort localization, and increased productivity.

Q: Who is adopting Omniverse Blueprints?
A: Developers at independent software vendors (ISVs) and production services agencies, such as Accenture Song, GRIP, Monks, WPP, and Collective World.

Riot Games Unveils Punchy New Visual Identity

Phil
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Riot Games Unveils Punchy New Visual Identity

Developer Riot Games has unveiled a fresh design system, unifying its diverse entertainment portfolio into an evolved master brand.

A New Design System for a Unifying Brand

Iconic brands all have a strong sense of identity and Riot’s new design system is no different. From in-game visuals to live events, the new diverse design system is built to be an adaptable and dynamic tool with a playful spirit at its core, never losing sight of Riot’s unique identity.

Creating a Sense of Identity

Created by Stink Studios, the new design system began by defining Riot’s brand purpose. “From the start everything had to be about improving player experience,” Cameron Temple, executive creative director at Stink Studios tells Creative Bloq. “We looked closely at what makes Riot, Riot. The culture, the gaming worlds, the characters, and all the little details in between. From this we developed a single-minded strategy – Riot is a creator of worlds, in service to players. From here our design focus became about capturing the spirit of the games and reflecting that in the work.”

The Core of the Design System

Central to the new design system is Riot’s iconic fist bump logo, which has been part of its identity from the very start. “Elevated to a living symbol of approval, and a fist bump to the community,” the motif is just one of many references to Riot’s brand, including characters from its iconic IPs like League of Legends and Arcane.

Flexibility and Adaptability

Flexibility was a key component in designing the new brand system, ensuring that the Riot team could easily adopt and adapt the new style. “It was key for the brand to be used by anyone working at Riot Games, not just designers. So our design needed to be flexible for people who wanted to be more creative with it, while also working for those who needed more prescriptive guidance,” Cameron says.

Design Process

“We started the project by conducting a series of stakeholder interviews to get to the bottom of what the system needed to achieve, both from a creative point of view, but also a functional one. Striking this balance while retaining the creative ambition was a good challenge,” he adds.

Color Palette and Design Elements

The core color palette uses the brand’s signature ‘Riot Red’ alongside complimentary tones to add a sense of depth, while the secondary palette has a more expressive feel representing Riot’s diverse creative worlds. “Creating design examples and seeing it all come together in different expressions was a really satisfying moment. Applying the thinking to social posts, flags, merch and so on was a lot of fun,” Cameron says.

Conclusion

Riot’s new design system is a testament to the power of a unified brand identity. By creating a system that is adaptable, flexible, and true to the brand’s spirit, Riot has set itself up for success in the gaming and entertainment industries.

FAQs

Q: What is the purpose of Riot’s new design system?
A: The purpose of the new design system is to unify Riot’s diverse entertainment portfolio and create a single, cohesive brand identity.

Q: Who created the new design system?
A: The new design system was created by Stink Studios in collaboration with Riot Games.

Q: What are the key components of the design system?
A: The key components of the design system include the core color palette, secondary palette, and various design elements such as logos, typography, and graphics.

Q: What is the goal of the design system?
A: The goal of the design system is to create a flexible and adaptable brand identity that can be used across all of Riot’s entertainment platforms and properties.

Adobe’s Massive Black Friday Deal

Phil
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Adobe’s Massive Black Friday Deal

Adobe Black Friday Deal: 50% Off Creative Cloud for the Next 12 Months

The annual Adobe Black Friday deal has begun, and this year it’s a big one: 50% off Creative Cloud for the next 12 months if you sign up before the end of November. The takes the price of an all-apps subscription in the US down from $59.99 to $29.99 per month for a 12-month saving of $299. Similar discounts are available in other regions.

What Does the Deal Include?

A Creative Cloud All-Apps plan includes more than 20 creative programs, from Photoshop for digital art and design and Lightroom for photo editing to Illustrator for vector design and Premiere Pro and After Effects for video editing. With this deal, you’ll also get access to the premium version of Adobe Express, generative credits for a range of new AI tools powered by Adobe Firefly, and 100GB of cloud space storage.

Is Adobe Creative Cloud Right for You?

If you’re still unsure whether Adobe’s software is for you, the usual seven-day free trial still applies, so you can always check out the apps and cancel before you get charged.

Who Does the Adobe Black Friday Deal Apply To?

The Adobe Black Friday deal applies only to new subscribers for their first year. After 12 months, your subscription charge will increase to the standard price, although you can always cancel at that point and see if Adobe offers a discount. There are also Black Friday deals for students and teams.

Why is Adobe Creative Cloud so Popular?

Adobe’s Creative Cloud apps are popular partly because many creatives simply have to use them since they’re the programs most used in their fields. However, in most cases, Adobe’s software is simply the best on the market. Every year, it introduces new features to improve the apps, keeping them ahead of the competition – most recently with many generative AI tools. As a subscriber, you automatically get access to all new features as soon as they’re released (or even before the full releases if you install the beta versions).

What are the Benefits of Adobe Creative Cloud?

Many Adobe apps integrate well with each other, allowing creatives to work across a seamless ecosystem. And as well as the 20 plus software programs themselves, users also get access to handy resources like Adobe Fonts, Adobe Portfolio, Adobe Stock, tutorials, and cloud storage space for storing creations.

Conclusion

If you’ve been waiting all year for the right moment to subscribe to Adobe’s industry-leading software, now’s the time. With 50% off the all-apps subscription, you can experience the full range of Adobe’s creative programs for an unbeatable price.

FAQs

Q: Is the Adobe Black Friday deal available in my region?

A: Yes, the deal is available in various regions, including the US, UK, Canada, and more. Check Adobe’s website for specific pricing and availability in your area.

Q: Can I cancel my subscription after 12 months?

A: Yes, you can cancel your subscription at any time. However, keep in mind that you’ll no longer have access to the exclusive features and updates available to subscribers.

Q: Can I sign up for a single-app subscription instead?

A: Yes, single-app subscriptions are available, but they don’t come with the same discounts as the all-apps subscription. The all-app package is the best value for money, especially considering the new features and updates you’ll receive as a subscriber.

Q: What happens to my subscription after 12 months?

A: After 12 months, your subscription charge will increase to the standard price. However, you can always cancel at that point and see if Adobe offers a discount.

C-Suite vs. Practitioners

Avery Winslow
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C-Suite vs. Practitioners

A report by Publicis Sapient sheds light on the disparities between the C-suite and practitioners, dubbed the “V-suite,” in their perceptions and adoption of generative AI.

The report reveals a stark contrast in how the C-suite and V-suite view the potential of generative AI. While the C-suite focuses on visible use cases such as customer experience, service, and sales, the V-suite sees opportunities across various functional areas, including operations, HR, and finance.

Risk Perception

The divide extends to risk perception as well. Fifty-one percent of C-level respondents expressed more concern about the risk and ethics of generative AI than other emerging technologies. In contrast, only 23 percent of the V-suite shared these worries.

Simon James, Managing Director of Data & AI at Publicis Sapient, said: “It’s likely the C-suite is more worried about abstract, big-picture dangers – such as Hollywood-style scenarios of a rapidly-evolving superintelligence – than the V-suite.”

Uncertainty Surrounding Maturity

The report also highlights the uncertainty surrounding generative AI maturity. Organisations can be at various stages of maturity simultaneously, with many struggling to define what success looks like. More than two-thirds of respondents lack a way to measure the success of their generative AI projects.

Navigating the Generative AI Landscape

Despite the C-suite’s focus on high-visibility use cases, generative AI is quietly transforming back-office functions. More than half of the V-suite respondents ranked generative AI as extremely important in areas like finance and operations over the next three years, compared to a smaller percentage of the C-suite.

The Path Forward

To harness the full potential of generative AI, the report recommends a portfolio approach to innovation projects. Leaders should focus on delivering projects, controlling shadow IT, avoiding duplication, empowering domain experts, connecting business units with the CIO’s office, and engaging the risk office early and often.

Daniel Liebermann, Managing Director at Publicis Sapient, commented: “It’s as hard for leaders to learn how individuals within their organisation are using ChatGPT or Microsoft Copilot as it is to understand how they’re using the internet.”

Conclusion

The report concludes with five steps to maximise innovation: adopting a portfolio approach, improving communication between the CIO’s office and the risk office, seeking out innovators within the organisation, using generative AI to manage information, and empowering team members through company culture and upskilling.

As generative AI continues to evolve, organisations must bridge the gap between the C-suite and V-suite to unlock its full potential. The future of business transformation lies in harnessing the power of a decentralised, bottom-up approach to innovation.

FAQs

Q: What is the main difference between the C-suite and V-suite perspectives on generative AI?
A: The C-suite focuses on visible use cases, while the V-suite sees opportunities across various functional areas.

Q: What percentage of C-level respondents expressed concern about the risk and ethics of generative AI?
A: Fifty-one percent.

Q: What is the recommended approach to innovation projects for generative AI?
A: A portfolio approach, focusing on delivering projects, controlling shadow IT, avoiding duplication, empowering domain experts, connecting business units with the CIO’s office, and engaging the risk office early and often.

Q: What are the five steps to maximise innovation with generative AI?
A: Adopting a portfolio approach, improving communication between the CIO’s office and the risk office, seeking out innovators within the organisation, using generative AI to manage information, and empowering team members through company culture and upskilling.

Differentiable Self-Organizing Systems

Parker Lennox
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Differentiable Self-Organizing Systems

Here is the rewritten article:

How can we construct robust, general-purpose self-organising systems?

Self-organisation is omnipresent on all scales of biological life. From complex interactions between molecules forming structures such as proteins, to cell colonies achieving global goals like exploration by means of the individual cells collaborating and communicating, to humans forming collectives in society such as tribes, governments or countries. The old adage “the whole is greater than the sum of its parts”, often ascribed to Aristotle, rings true everywhere we look.

The articles in this thread focus on practical ways of designing self-organizing systems. In particular we use Differentiable Programming (optimization) to learn agent-level policies that satisfy system-level objectives. The cross-disciplinary nature of this thread aims to facilitate ideas exchange between ML and developmental biology communities.

Articles & Comments

Growing Neural Cellular Automata

Building their own bodies is the very first skill all living creatures possess. How can we design systems that grow, maintain and repair themselves by regenerating damages? This work investigates morphogenesis, the process by which living creatures self-assemble their bodies. It proposes a differentiable, Cellular Automata model of morphogenesis and shows how such a model learns a robust and persistent set of dynamics to grow any arbitrary structure starting from a single cell.

Self-classifying MNIST Digits

This work presents a follow up to Growing Neural CAs, using a similar computational model for the goal of digit “self-classification”. The authors show how neural CAs can self-classify the MNIST digit they form. The resulting CAs can be interacted with by dynamically changing the underlying digit. The CAs respond to perturbations with a learned self-correcting classification behaviour.

Self-Organising Textures

Here the authors apply Neural Cellular Automata to a new domain: texture synthesis. They begin by training NCA to mimic a series of textures taken from template images. Then, taking inspiration from adversarial camouflages which appear in nature, they use NCA to create textures which maximally excite neurons in a pretrained vision model. These results reveal that a simple model combined with well-known objectives can lead to robust and unexpected behaviors.

Adversarial Reprogramming of Neural Cellular Automata

This work takes existing Neural CA models and shows how they can be adversarially reprogrammed to perform novel tasks. MNIST CA can be deceived into outputting incorrect classifications and the patterns in Growing CA can be made to have their shape and colour altered.

Get Involved

The Self-Organizing systems thread is open to articles exploring differentiable self-organizing sytems. Critical commentary and discussion of existing articles is also welcome. The thread is organized through the open #selforg channel on the Distill slack. Articles can be suggested there, and will be included at the discretion of previous authors in the thread, or in the case of disagreement by an uninvolved editor.

About the Thread Format

Part of Distill’s mandate is to experiment with new forms of scientific publishing. We believe that that reconciling faster and more continuous approaches to publication with review and discussion is an important open problem in scientific publishing.

Threads are collections of short articles, experiments, and critical commentary around a narrow or unusual research topic, along with a slack channel for real-time discussion and collaboration. They are intended to be earlier stage than a full Distill paper, and allow for more fluid publishing, feedback, and discussion. We also hope they’ll allow for wider participation. Think of a cross between a Twitter thread, an academic workshop, and a book of collected essays.

Threads are very much an experiment. We think it’s possible they’re a great format, and also possible they’re terrible. We plan to trial two such threads and then re-evaluate our thought on the format.

Conclusion

The articles in this thread demonstrate the potential of Differentiable Programming to design self-organizing systems that can learn and adapt in complex environments. By applying these techniques to various domains, we can unlock new possibilities for understanding and influencing the behavior of complex systems.

FAQs

Q: What is Differentiable Programming?

A: Differentiable Programming is a way of using optimization techniques to learn agent-level policies that satisfy system-level objectives.

Q: What is the purpose of this thread?

A: The purpose of this thread is to explore practical ways of designing self-organizing systems using Differentiable Programming.

Q: Can I contribute to this thread?

A: Yes, you can suggest articles or comment on existing articles through the #selforg channel on the Distill slack.

Jaguar’s Bold New Logo Won’t Please Everyone

Phil
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Jaguar’s Bold New Logo Won’t Please Everyone

Jaguar Unveils Bold New Logo and Brand Identity

We’ve seen a huge amount of new car logos hit the road over the last few years, with everyone from the likes of Kia to Rolls-Royce debuting new identities. And now, Jaguar has presented what might be the boldest reimagining yet, complete with a brand new logo, wordmark, and typeface.

A New Era for Jaguar

During a media briefing today, Jaguar unveiled what it calls an "exuberant, modernist, and compelling" new look. And perhaps anticipating the controversy such a comprehensive rebirth might prompt, the brand added that when it comes to its visual identity, it is "not afraid to polarise". So while the new wordmark, which combines upper and lowercase letters might look like one of the best logos for some, it could prove too much to stomach for others.

The New Logo

At the heart of the new look is two new logos. Most notable is the minimal new wordmark which, with its slim, curved letters, somewhat resembles the logo for the Dune movies. Jaguar calls the wordmark "a powerful celebration of modernism – geometric form, symmetry and simplicity – demonstrating the unexpected by seamlessly blending upper and lowercase characters in visual harmony."

The Monogram

Also present is a circular ‘JR’ monogram that looks like it belongs on a signet ring. "The monogram is a code for expression and a signifier of a completed work. It is used as a flourish or finishing touch," Jaguar says.

The Cars

The cars themselves will continue to feature the classic ‘leaper’ logo, which is good news since it’s one of the best car logos on the road today. But this fresh iteration incorporates the new brand identity’s ‘strikethrough’ graphic code, in which it’s rendered on a series of horizontal lines.

Conclusion

Jaguar’s new branding is very much of the minimal, flat design style that was all the rage a few years back. While it may not appeal to everyone, it’s certainly an extraordinary bold rebrand. Time will tell how the rebrand is represented on the cars themselves.

FAQs

Q: What is the inspiration behind Jaguar’s new logo?
A: The new logo is inspired by Jaguar’s heritage and its founder, Sir William Lyons, who emphasized the importance of creativity and innovation.

Q: What is the significance of the new wordmark?
A: The new wordmark is a powerful celebration of modernism, showcasing geometric form, symmetry, and simplicity.

Q: Will the new logo be used on all Jaguar cars?
A: The classic ‘leaper’ logo will continue to be used on Jaguar cars, with the new brand identity’s ‘strikethrough’ graphic code incorporated into the design.

Prepare Now for AI-Driven Workflow Disruption

Emerson Blake
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Prepare Now for AI-Driven Workflow Disruption

Autonomous Agents: The Future of AI

If you have used an AI chatbot, you have experienced firsthand how convenient it is to have an assistant who can answer any questions instantaneously. Now imagine if that assistant could understand and act on your needs without you telling it what to do — meet autonomous agents or agentic AI.

The Rise of Agentic AI

Although this vision may seem like something out of a sci-fi movie, many companies are working on making agentic AI a reality, with enterprise solutions already being released. Deloitte’s 2025 TMT Predictions report predicts that 25% of companies that use generative AI will launch agentic AI pilots by 2025 and 50% by 2027.

Investments and Growth

Furthermore, the report suggests investors have contributed over $2bn to agentic AI startups over the last two years, with efforts concentrated in the enterprise market. So, with such rapid growth and robust investments, how much will agents impact workers?

What is Agentic AI?

Agentic AI refers to assistants that make decisions independently from human intervention, choosing what actions to take to accomplish a particular goal established by a human. They differ from copilots, which respond to human requests to act.

Challenges and Limitations

Because agentic AI performs independently, the technology must be able to perform tasks reliably all the time — and the technology isn’t quite at the required level yet.

Impact on Workers

The report says an agentic coding engineer, which would still require some human supervision, will be achievable by 2025. As seen in the chart below, a completely agentic coding engineer is so far away that there is no predicted date:

GenAI agents

Deloitte

Boosting Productivity

The report also delineates how the impacts of agentic AI could be “enormous” because there are one billion knowledge workers globally and stagnant productivity growth in the US. Productivity had only increased by 0.5% from 2019 to 2023 compared to 0.8% growth from 1987 to 2023.

Conclusion

Agentic AI represents a new frontier for AI. However, the technology is built on pre-existing foundations, including large language models, enterprise applications, the internet, and multimodal capabilities. Ultimately, the report suggests agentic AI will be valuable despite being at an early stage of development and adoption.

Frequently Asked Questions

Q: What is agentic AI?
A: Agentic AI refers to assistants that make decisions independently from human intervention, choosing what actions to take to accomplish a particular goal established by a human.

Q: How will agentic AI impact workers?
A: The report suggests that agentic AI will have a significant impact on workers, particularly in areas such as customer support, cybersecurity, and regulatory compliance.

Q: When can we expect to see agentic AI in action?
A: The report predicts that 25% of companies that use generative AI will launch agentic AI pilots by 2025 and 50% by 2027.

Q: What are the challenges and limitations of agentic AI?
A: The technology must be able to perform tasks reliably all the time, which is currently not the case.

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