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The Space Force shares a photo of Earth taken by the X-37B space plane.

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Space Force Captures Rare Photo of X-37B Space Plane in Action

X-37B Space Plane Conducts Experimental Aerobraking Maneuvers

The United States Space Force has published a rare photo of the secretive X-37B space plane, taken from a camera mounted on the spacecraft while it was high above the Earth. This is only the second time the X-37B has been spotted in space, with the first instance being its deployment from a Falcon Heavy’s upper stage during its December 2023 launch.

Experimental Aerobraking Maneuvers

The Space Force snapped the photo during experimental "first-of-kind" aerobraking maneuvers, which aim to safely change the plane’s orbit using minimal fuel. The Air Force explained in October that this process would involve a series of passes using the drag of Earth’s atmosphere, and once complete, the plane would resume its other experiments before de-orbiting.

X-37B’s Seventh Mission

This is the X-37B’s seventh mission, with its sixth mission concluding in November 2022, lasting about two-and-a-half years (or 908 days) and being its longest mission to date. Prior to its launch, the Space Force described mission goals that included operating in new orbital regimes and testing future space domain awareness technologies. The mission also involved an onboard NASA experiment involving plant seeds’ radiation exposure during long spaceflight missions.

Conclusion

The X-37B’s experimental aerobraking maneuvers demonstrate the Space Force’s commitment to advancing the capabilities of its spacecraft and pushing the boundaries of what is possible in space. As the X-37B continues to evolve and improve, it is likely to play an increasingly important role in the United States’ space-based operations.

Frequently Asked Questions

Q: What is the X-37B space plane?
A: The X-37B is a secretive space plane developed by the United States Air Force.

Q: What is the purpose of the X-37B’s aerobraking maneuvers?
A: The X-37B’s aerobraking maneuvers aim to safely change its orbit using minimal fuel.

Q: How long has the X-37B been in operation?
A: The X-37B has been in operation since its first mission, which began in 2010.

Q: What is the X-37B’s longest mission to date?
A: The X-37B’s longest mission to date was its sixth mission, which lasted about two-and-a-half years (or 908 days).

The Era of Citizen Developers

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Can Citizen Developers Now Use Generative AI to Build Applications?

Generative AI (Gen AI) has revolutionized the way professional software developers create applications by eliminating much of the grunt work. The question is: can citizen developers also benefit from this new paradigm in code creation?

Some experts believe so. Over the coming year, citizen developers will deliver 30% of Gen AI-infused automation apps, according to Craig Le Clair, principal analyst with Forrester. They have the necessary domain expertise to envision and develop these solutions, and require concerted training to ensure the safely provisioned and controlled proliferation of AI models and copilot platforms.

The Current State of Gen AI for Citizen Developers

However, one big issue is that citizen developers might not be ready to handle bare-metal Gen AI when creating applications. While Gen AI is breaking down barriers by allowing them to experiment and rapidly create no-code applications just by describing what they need in natural language, a hybrid approach remains essential.

Designing User Interfaces and Workflows

A good analogy is how a word processor allows users to switch between draft mode and full WYSIWYG layout depending on editing needs. Many tasks, such as designing user interfaces and workflows, are better suited to visual representation. Citizen developers need to extend their apps easily, which is why a hybrid approach is necessary.

Customization and Governance

Another issue is customization. Kawasaki said citizen developers need to extend their apps easily. While they could directly modify generated code, it’s easier for humans and AI to update declarative models, which are at the heart of no-code platforms. Additionally, within enterprise environments, citizen developers must consider design trade-offs, best practices, and compliance with governance, security, and regulatory standards.

Lessons from the Professionals

Gen AI-powered coding has proven to be a preferred solution for many developers. This proliferation offers important pointers for non-professionals. Gen AI coding for developers has rapidly taken off because it literally speaks their language — the language of procedural code. The code may be created differently than traditional software development, but once generated, the code output fits naturally into existing development methodologies and DevOps practices.

Risks and Considerations

However, the use of Gen AI by professional developers has highlighted some important risks. While Gen AI coding is powerful, it’s the responsibility of the enterprise to ensure proper governance to mitigate risks. Without proper oversight, AI-generated code can introduce bugs, security vulnerabilities, and inconsistencies across applications. Lack of standardization also poses risks in Gen AI coding environments.

Conclusion

In conclusion, while Gen AI has the potential to revolutionize the way citizen developers create applications, it’s essential to recognize the challenges and limitations that come with its use. By understanding the current state of Gen AI and its limitations, we can better navigate the complexities of its implementation and ensure that it is used responsibly.

FAQs

Q: Can citizen developers use Gen AI to build applications?
A: Yes, but with proper training and governance to ensure the safely provisioned and controlled proliferation of AI models and copilot platforms.

Q: What are the challenges of using Gen AI for citizen developers?
A: One big issue is that citizen developers might not be ready to handle bare-metal Gen AI when creating applications, and they need to extend their apps easily.

Q: What are the risks of using Gen AI?
A: Gen AI coding can introduce bugs, security vulnerabilities, and inconsistencies across applications, and lack of standardization poses risks in Gen AI coding environments.

Q: How can enterprises ensure proper governance of Gen AI?
A: Enterprises must ensure proper oversight to mitigate risks, and invest in composable architectures and curated marketplaces to reduce the risk of data inconsistency, variations in workflows, and uneven usability standards.

This mental health chatbot aims to fill the counseling gap at understaffed schools.

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Supporting Student Mental Health with AI-Powered Chatbot

Introducing Sonny, the Wellbeing Companion

As school districts struggle to support the mental health of their students, a startup called Sonar Mental Health has built a "wellbeing companion" called Sonny to help. Sonny is a chatbot that relies on a combination of human staff and AI. When students text their questions to Sonny, the AI suggests a response, but it’s humans who are ultimately responsible for the message.

How Sonny Works

Sonar signed its first school partnership in January 2024 and says it’s now available to more than 4,500 middle and high school students across nine districts. The company says the chats are currently being monitored by a team of six people with backgrounds in psychology, social work, and crisis-line support.

CEO’s Clarification

CEO Drew Bavir told the Journal that he makes it clear to students and schools that Sonny isn’t a therapist, and that Sonar staffers will work with schools and parents to find therapists for students when appropriate.

Addressing the Counselor Shortage

A big reason why this approach might appeal to school districts is a current shortage in counselors. The Education Department says 17% of high schools don’t have a high school counselor at all. This shortage can make it difficult for schools to provide adequate mental health support to their students.

Conclusion

Sonny, the wellbeing companion, offers a potential solution to this problem by providing students with a convenient and accessible way to get help when they need it. By combining AI and human support, Sonar Mental Health is helping to bridge the gap in mental health services and support for students.

Frequently Asked Questions

Q: What is Sonny?
A: Sonny is a chatbot that relies on a combination of human staff and AI to provide support and guidance to students.

Q: How does Sonny work?
A: When students text their questions to Sonny, the AI suggests a response, but it’s humans who are ultimately responsible for the message.

Q: Is Sonny a therapist?
A: No, Sonny is not a therapist. Sonar staff will work with schools and parents to find therapists for students when appropriate.

Q: How many students can Sonny support?
A: Sonar says Sonny is currently available to more than 4,500 middle and high school students across nine districts.

IKO: Lessons Learned

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Getting Started with Helm: Installing the InterSystems Kubernetes Operator (IKO)

What is Helm?

Helm is a package manager for Kubernetes, similar to the InterSystems Package Manager (IPM) for IRIS. It facilitates the installation of applications on a Kubernetes platform, making it suitable for development, testing, or production environments.

Understanding the IKO Documentation

The IKO documentation is robust, comprising about 50 pages. For beginners, this can be overwhelming. As the saying goes, "how do you eat an elephant? One bite at a time." Let’s start with the first bite: Helm.

The Chart

The chart, located in the iris_operator folder, is necessary for IKO installation. It contains various files, including Chart.yaml, values.yaml, and templates. We will focus on the values.yaml file, as it is the most important aspect of the installation process.

values.yaml

The values.yaml file contains five key fields that require attention:

  • operator.registry
  • operator.repository
  • operator.tag
  • imagePullSecrets.name[0]
  • imagePullPolicy

These fields specify the IKO image, registry, repository, and tag, as well as the image pull secrets and policy.

Configuring the Image

  • Specify your IKO image details in the registry, repository, and tag fields.
  • If using the InterSystems Container Registry (ICR), you can leave the fields as is.
  • If using a private repository, you will need to specify your access details.

imagePullPolicy

The imagePullPolicy field can be set to Always, IfNotPresent, or Never. For more information, refer to the Kubernetes documentation.

Installing IKO with Helm

To install IKO, navigate to the iris_operator folder and run the following command:

helm install intersystems iris_operator

If you are in a different directory, you can specify the path:

helm install intersystems iris_operator_amd-3.6.7.100/chart/iris-operator

Verifying the Installation

After a successful installation, you will receive a message indicating that the installation was successful. You can verify the deployment by running the following command:

kubectl --namespace=default get deployments -l "release=intersystems, app=iris-operator"

Conclusion

In this article, we have covered the basics of Helm and its role in installing the InterSystems Kubernetes Operator (IKO). We have also explored the values.yaml file and its importance in the installation process. In the next article, we will put the IKO to use.

FAQs

Q: What is Helm?
A: Helm is a package manager for Kubernetes, similar to the InterSystems Package Manager (IPM) for IRIS.

Q: What is the IKO?
A: The IKO is the InterSystems Kubernetes Operator, which facilitates the installation of applications on a Kubernetes platform.

Q: How do I install IKO with Helm?
A: To install IKO with Helm, navigate to the iris_operator folder and run the helm install command.

Q: What is the values.yaml file?
A: The values.yaml file is a configuration file that specifies the IKO image, registry, repository, and tag, as well as the image pull secrets and policy.

VAST Data Expands Platform With Block Storage and Real-Time Event Streaming

VAST Data Unveils Unifying Real-Time Data Processing and Storage

VAST Data, a company specializing in high-performance data platforms for AI and large-scale data processing, has made significant announcements related to unifying real-time data processing and storage.

Universal Storage Capabilities

The company has added universal storage capabilities to its flagship Vast DataStore offering, making it the industry’s first "fully unified" data platform for artificial intelligence workloads. This upgrade aims to eliminate the need for multiple, separate storage systems, allowing businesses to consolidate their infrastructure and simplify data management. The company claims that the new capabilities cater to all types of workload, without any trade-offs in performance, costs, or scalability.

Key Features

  • Support for environments such as VMware, Hyper-V, and other hypervisors
  • Optimization for Kubernetes and containerized applications
  • Boot from SAN, enabling businesses to deploy and manage servers without relying on local disks, improving redundancy, simplifying provisioning, and enhancing disaster recovery
  • Block storage functionality, available next month as part of the Vast Data Platform

Limitations

While VAST’s move toward unified storage is promising, its block storage capabilities are still evolving. For example, the platform only supports NVMe-over-Ethernet currently, lacks traditional Fibre Channel and iSCSI support, and does not offer remote direct memory access (RDMA). However, VAST Data has road-mapped some of these features for future releases.

VAST Event Broker

In another major announcement, VAST Data unveiled VAST Event Broker – a real-time event streaming engine that unifies transactional and analytical data. The platform leverages AI agents to dynamically act on incoming data, delivering real-time intelligence and automation.

Key Features of VAST Event Broker

  • More than 10x the performance of legacy Kafka implementations, processing over 500 million messages per second and providing unlimited linear scalability
  • Simplifies data management by bringing transactional, analytical, AI, and real-time streaming workloads under a single architecture
  • Enables real-time data processing, analytics, and AI workloads to be run on a single platform

Conclusion

VAST Data’s latest announcements demonstrate its commitment to unifying real-time data processing and storage, enabling businesses to streamline their infrastructure and simplify data management. The company’s innovative solutions, including its VAST Event Broker, are poised to revolutionize the way organizations process and analyze data, ultimately driving faster, more accurate decision-making and unlocking data-driven growth.

FAQs

Q: What are the key features of VAST Data’s universal storage capabilities?
A: The key features include support for environments such as VMware, Hyper-V, and other hypervisors, optimization for Kubernetes and containerized applications, Boot from SAN, and block storage functionality.

Q: What are the limitations of VAST Data’s block storage capabilities?
A: The platform currently only supports NVMe-over-Ethernet, lacks traditional Fibre Channel and iSCSI support, and does not offer remote direct memory access (RDMA). However, VAST Data has road-mapped some of these features for future releases.

Q: What is VAST Event Broker, and what are its key features?
A: VAST Event Broker is a real-time event streaming engine that unifies transactional and analytical data. Its key features include more than 10x the performance of legacy Kafka implementations, simplifying data management, and enabling real-time data processing, analytics, and AI workloads to be run on a single platform.

Q: When will the VAST Event Broker be available?
A: The VAST Event Broker is scheduled to be available in March.

Hades II Just Keeps Getting Better

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Hades II Just Got a Major Update, and It’s Better Than Ever

A New Region and Boss, and a Whole Lot More

I jumped back into Hades II, the action-packed roguelike from Supergiant Games, after its second major update, and I’m impressed by the progress the studio has made. The update added a new region, a new boss, and a ton of smaller details that have made the game feel even better to play.

The Big Additions

The big additions are impressive. Hades II initially launched with six regions – four for an Underworld route and two for a "surface" route – and with each major update, Supergiant has added a new region with new enemies, characters, and music to round out that surface route. The first major update, which came out in October, added the game’s first new region, Mount Olympus, and it feels as epic as Mount Olympus should. It has grand architecture, fearsome enemies, and a fiery boss fight against Prometheus, all backed by an incredible orchestral soundtrack.

Witch-y Mechs and More

That update also added the game’s sixth and final weapon – a witch-y, Hades-style interpretation of a mech suit. Seriously: your primary attack is punching baddies with giant fists while your special attack shoots projectiles that home in on nearby targets. You also have cool wings.

Smaller But Significant Changes

In the second major update, there’s a new region and boss, too, but I’ve also noticed a lot of smaller details that feel just as impactful. For example, the Altar of Ashes, a place where you pick from various passive effects in the form of arcana cards that can help your runs, got a visual redesign to add intricately-illustrated custom cards. (One of them features Theseus and the Minotaur, who you may remember as bosses from the first Hades, in thongs, lol.) I also spotted a charming new portrait for Melinoë, the game’s protagonist, that added some levity to a character that’s usually pretty serious.

A Game that’s Getting Better with Time

Overall, the changes have made the game feel better to play over time – and browsing patch notes, Supergiant uses an emoji to indicate which changes are inspired by community feedback, which I think is a good way to acknowledge how players are contributing to the game, which is one of the main benefits of this type of early access release. (I should also acknowledge that Hades II has the advantage of building from the already-great foundation of the first Hades.)

Conclusion

Hades II might not launch in 1.0 for a long time. Supergiant hasn’t committed to a timeframe for that, and it’s still working on a third major update that’s set to release "some months from now." Because of the success of Supergiant’s other games, like Bastion and Transistor, the studio probably doesn’t need to rush. But given how it’s treated Hades II’s early access so far, I’m fine if Supergiant takes its time.

Frequently Asked Questions

Q: Is Hades II still in early access?
A: Yes, Hades II is still in early access and is expected to continue to receive updates and improvements.

Q: How often do I need to play to keep up with the changes?
A: It’s not necessary to play constantly to keep up with the changes, but frequent play sessions can help you stay current with the latest updates.

Q: Is Hades II worth playing?
A: Yes, Hades II is worth playing, even in its current state, due to its engaging gameplay and constant improvements.

10 Key Reasons AI Went Mainstream Overnight

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The Rise of Generative AI: 10 Key Factors Contributing to Its Rapid Advancement

The generation of AI has taken off at an unprecedented rate, leaving many of us wondering what drove this rapid advancement. As someone who has worked with AI for decades, I have witnessed the transformation firsthand. In this article, I will explore the ten key factors that have contributed to the overwhelming adoption of generative AI, from fundamental innovations to competitive market pressure and continuous innovation and investment.

Phase I: Fundamental Innovations

The 2020s marked an era of fundamental AI innovation, taking AI from solving specific problems to working on almost anything. Three key factors contributed to this phase:

  1. Advancements in Transformer Models: Google’s "Attention Is All You Need" paper proposed a model called "self-attention" that allows AIs to focus on important words, enabling them to understand context.
  2. Widely-trained Foundation Models: The transformer approach enabled researchers to train AIs on broad collections of information, determining context from the information itself.
  3. Breakthroughs in Hardware (GPUs and TPUs): The need for massive computing capability to perform sentence-wide transformation calculations led to the development of software systems based on the transformer model and world-scale training datasets.

Phase II: The Rise of Generative AI

The swift adoption of AI tools like ChatGPT has transformed the IT industry, with many vendors incorporating AI features into their products, changing workflow patterns. The following factors contributed to this phase:

  1. Competitive Market Pressure: The sudden rise of OpenAI, Google, Microsoft, Meta, Amazon, and Apple, among others, created a competitive market, driving innovation and investment.
  2. Legislative and Regulatory Lag: Governments struggled to keep pace with the rapid development of AI, leading to a lack of clear regulations, making it difficult to ensure AI’s responsible development.
  3. Continuous Innovation and Investment: The virtuous cycle of innovation and investment has driven the growth of AI, with companies like OpenAI, Google, and Microsoft continuing to invest in AI research and development.

Phase III: The Future of AI

As we look to the future, we can expect further advancements in AI, including:

  1. Multimodal AI: Combining text, images, video, and audio to create more comprehensive AI capabilities.
  2. Autonomous Agents: Developing AI that can act independently, making decisions without human intervention.
  3. Ethical and Regulatory Concerns: Addressing the need for clear regulations and guidelines for the development and use of AI.

Conclusion

The rapid rise of generative AI has been driven by a combination of fundamental innovations, competitive market pressure, and continuous innovation and investment. As we look to the future, we can expect AI to continue to shape our lives, from vacuuming our floors to making our morning coffee. The question remains: what will be the next breakthrough, and how will it change our world?

FAQs

Q: What are the key factors contributing to the rapid advancement of generative AI?
A: Ten key factors, including fundamental innovations, competitive market pressure, and continuous innovation and investment.

Q: What are some of the potential applications of AI in the future?
A: Multimodal AI, autonomous agents, and ethical and regulatory concerns, among others.

Q: How do you see AI shaping the future of our daily lives?
A: AI will continue to transform our lives, making tasks more efficient and convenient, from household chores to personal assistance.

Maximize Your File Server Data’s Potential on Amazon FSx for Windows

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Overview of Amazon Q Business and Amazon FSx for Windows File Server

Organizations need efficient ways to access and analyze their enterprise data. Amazon Q Business addresses this need as a fully managed generative AI-powered assistant that helps you find information, generate content, and complete tasks using enterprise data. It provides immediate, relevant information while streamlining tasks and accelerating problem-solving.

Supported Document Types

Amazon Q boasts impressive versatility, supporting a wide range of document types stored at various places in your environment, including Windows Share (FSx for Windows File Server). Amazon Q can ingest and understand common formats like plaintext, PDF, HTML, XML, and JSON to Microsoft formats like Excel, Word, and PowerPoint. This provides a comprehensive search experience for your enterprise users.

Secure Access with Supported Authentication Types

Security is job zero at AWS, and Amazon Q has been built keeping that in mind. It supports a variety of authentication types, seamlessly integrating with your existing identity management systems. Whether you use single sign-on (SSO) or a custom authentication solution, Amazon Q can adapt to your specific needs.

Fine-Grained Control with ACLs and Identity Crawling

For organizations with highly sensitive data, Amazon Q offers an extra layer of security. Amazon Q Business supports crawling access control lists (ACLs) for document security by default. When you connect an Amazon FSx (Windows) data source to Amazon Q Business, it crawls ACL information attached to a document (user and group information) from the directory service of the Amazon FSx instance.

Overview of Solution

The following diagram shows a high-level architecture of how AWS Managed Active Directory users, through AWS IAM Identity Center, can access and interact with an Amazon Q Business application. This enables an authenticated user to securely and privately interact with the application and gain insights from the enterprise data stored in FSx for Windows File Server, using the Amazon Q Business web experience from their web browser.

Prerequisites

To implement this solution, you should have an AWS account with administrative privileges. Follow the instructions in the GitHub repository’s README file to provision the infrastructure required for exploring the Amazon Q connector for FSx for Windows File Server.

Create an Amazon Q Business Application

Complete the following steps to create a new Amazon Q Business application:

  1. On the Amazon Q Business console, choose Applications in the navigation pane.
  2. Choose Create application.

Troubleshooting

If you encounter issues during the setup or operation of your Amazon Q Business application with FSx for Windows File Server, refer to the detailed troubleshooting guide in the README file. The guide provides solutions for common configuration challenges and operational issues you might experience.

Conclusion

In this post, we provided an overview of the Amazon Q FSx connector and how you can use it for safe and seamless integration of generative AI assistance with your enterprise data source. By using Amazon Q in your organization, you can enable employees to be more data-driven, efficient, prepared, and productive. Lastly, we demonstrated how using simple NLP search through Amazon Q Business enhances your ability to discover insights from your enterprise data quicker and respond to your needs faster.

Clean Up

To avoid ongoing charges, we recommend cleaning up the resources you created while following this guide. For step-by-step cleanup instructions, refer to the README file.

About the Authors

Manjunath Arakere is a Senior Solutions Architect on the Worldwide Public Sector team at AWS, based in Atlanta, Georgia. He partners with AWS customers to design and scale well-architected solutions, supporting their cloud migrations and modernization initiatives.

Imtranur Rahman is an experienced Sr. Solutions Architect in WWPS team with 14+ years of experience. Imtranur works with large AWS Global SI partners and helps them build their cloud strategy and broad adoption of Amazon’s cloud computing platform.

FAQs

Q: What is Amazon Q Business?
A: Amazon Q Business is a fully managed generative AI-powered assistant that helps you find information, generate content, and complete tasks using enterprise data.

Q: What is Amazon FSx for Windows File Server?
A: Amazon FSx for Windows File Server is a fully managed Windows file system that provides high-performance file storage for Windows-based applications.

Q: How does Amazon Q Business support document security?
A: Amazon Q Business supports crawling access control lists (ACLs) for document security by default, ensuring that users can only access documents they are authorized to access.

Q: What authentication types are supported by Amazon Q Business?
A: Amazon Q Business supports a variety of authentication types, including single sign-on (SSO) and custom authentication solutions.

Norway’s 1X is building a humanoid robot for the home.

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1X Unveils its Latest Home Robot, Neo Gamma

Norwegian robotics firm 1X unveiled its latest home robot, Neo Gamma, on Friday. The humanoid system will succeed Neo Beta, which debuted in August. Like its predecessors, the Neo Gamma is a prototype designed for testing in the home environment. Images of the robot show it performing a number of household tasks like making coffee, doing the laundry, and vacuuming.

A Softer, Friendlier Design

Neo Gamma represents a softer side of the humanoid industry — both figuratively and literally. 1X has built the robot to be welcoming, with a friendlier design and a suit made of knitted nylon. The latter is designed to reduce potential injuries that might arise from robot-to-human contact.

A Unique Approach

Neo Gamma arrives amid a sea of humanoids from companies like Agility, Apptronik, Boston Dynamics, Figure, and Tesla. While firms like Figure already have their robotic systems operating in a mock home environment within their lab, all have prioritized warehouse and factory deployment. 1X’s home-first approach makes it unique among its direct peers.

Challenges Ahead

Home robots have always been a tricky proposition. Beyond robotic vacuums produced by companies like iRobot, none have meaningfully penetrated the market. This isn’t from lack of trying — the technology simply isn’t there.

Safety Concerns

Home robots need to be useful, reliable, affordable, and significantly safer than their industrial counterparts. This is doubly the case given that age-tech is likely to be one of home humanoids’ key targets. As the average age of the population rises, independent living for older adults will become an increasingly important technology target.

AI and Teleoperation

Along with a softer shell, 1X points to advances in the Gamma’s on-board AI system as a key element in designing a safer robot. These systems need to be extremely aware of their surroundings so as to avoid causing potential harm to people or property. Teleoperation is an important part of the safety conversation, as well. While full autonomy is the end goal for most, it’s important that humans be able to take control of the system in a pinch, especially in the home.

Generative AI

Beyond its unique focus, 1X first crossed the radar of many in the industry when OpenAI was announced as an early backer. For many, the notion of embodied intelligence — AI with a physical presence — is the next logical step for the white-hot world of generative AI. OpenAI has since hedged its bets in the humanoid space, with both an investment in a competitor, Figure, as well as numerous rumors surrounding the ChatGPT maker’s own in-house robotics ambitions.

Conclusion

While we’re seeing the first humanoid deployments move beyond the pilot stage in industrial settings, these systems have a long way to go in terms of pricing, reliability, safety, and functionality before we can have a serious conversation about bringing them home.

FAQs

Q: How many Neo Gammas have been produced?

A: 1X has not disclosed how many Neo Gammas have been — or will be — produced over the course of the beta robot’s life.

Q: What is the purpose of the robot’s on-board AI system?

A: The AI system is designed to be extremely aware of its surroundings so as to avoid causing potential harm to people or property.

Q: What is the significance of teleoperation in the context of home robots?

A: Teleoperation is an important part of the safety conversation, as it allows humans to take control of the system in a pinch, especially in the home.

Q: What is the target market for home humanoids?

A: The target market for home humanoids is likely to be older adults, as the average age of the population rises, independent living will become an increasingly important technology target.

AI will take work, it will probably not take jobs

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How AI is Revolutionizing Typography

How useful is AI in typography?

The story is yet to be completely written with AI and typography, but at Monotype, we’re looking at a couple of different things. Over the past 25 years, the number of typefaces in the world has increased dramatically, on a scale of around 10 to 20x. So if you think of the turn of the century having roughly 20,000 digital files in the world, and now we’re probably globally approaching closer to a million or a million plus.

We all set type daily and we all interact with type throughout the year. AI can help us to navigate the bounty of typefaces as we move into the third decade of the 21st century. When you have that many digital typefaces, it’s often hard to find the one that you need. AI will help us to sort metadata, assign metadata, and make the discovery process much more seamless for the end user, because the end user has changed quite a bit in the 21st century. In the 20th century, typography was a highly specialized field, but in the 21st it’s for everyone.

Is AI going to take jobs in typography?

It will take work. It will probably not take jobs, at least not immediately. There are a lot of aspects of type design that are highly repetitive, time-consuming tasks. I’m thinking about the fitting and kerning of typefaces, the extending of typefaces into global scripts, the number of non-alphabetic and numeric characters that exist in a typeface. A lot of these things take a lot of time, but aren’t at the heart of the creative aspect of type design. And the idea of them being automated is probably a welcome thing for a lot of type designers. But I think the true creative aspect of it will still, for a long time, be the realm of actual human designers.

What is the role of human creativity nowadays?

This trends report is an introduction to what we’re doing throughout the rest of the year, and one of the first activations that we’re doing around the themes in the report is around typography and AI, and that’s the Human Types project. And what it looks at is precisely that question: what is it that we bring to the equation that a machine or machine learning or artificial intelligence won’t ever be able to replicate? We’ve engaged three type designers with very different points of view to put that question to them. We don’t pretend in the report to have all the answers, we know we’re going to get three very distinct views of what that looks like.

But one of the overarching ideas is that humans are the sort of creative chaos in a system, we are the ones who question and bring about different modes of thought by wanting to act in a contrary nature or a chaotic nature. Creativity is not a linear path. It’s a path or a journey that begins without knowing where it’s going to end. And I think that is the thing that we’ll continue to bring to the creative equation.

How do you see AI and the role of creativity evolving?

Right now, I am concentrating on the here and now. The story of typography over the last 600 years has been about this conversation between the typefaces themselves, the thing that we look at and read, and the technology that allows that to be made. So at the very beginning it was metal type, and then it evolved into machine set metal type and then into photo and then into digital.

I see AI and typography as being a continuation of that sort of ‘technology plus art’ narrative arc. The ways that it will affect typography are probably along the same triumvirate that has defined typography in the first 600 years, which is the form of type, how type is made, and the use of type – of being able to choose type, being able to use type well, to choose type appropriately, to pair type, to space type – all of the things that sort of govern what happens after we finish making type.

Conclusion

The role of AI in typography is still evolving, but one thing is clear: it will revolutionize the way we interact with type. From automating repetitive tasks to helping us discover new typefaces, AI will have a profound impact on the world of typography. But what about the role of human creativity? Will AI take over or complement our work? According to Charles Nix, the answer is clear: human creativity will continue to play a vital role in the world of typography.

FAQs

Q: Will AI replace human typographers?
A: No, AI will not replace human typographers. While it will automate some tasks, the creative aspects of type design will still require human input.

Q: How will AI affect the role of human creativity?
A: AI will not replace human creativity, but it will complement it. AI will help us to focus on the creative aspects of type design, while automating repetitive tasks.

Q: What is the future of typography?
A: The future of typography is uncertain, but one thing is clear: AI will play a significant role in it.