Search is evolving quickly, and traditional strategies alone are no longer enough to stay competitive. Today, users are increasingly turning to AI-powered platforms to find answers, discover brands, and make decisions. AI SEO services are designed to help businesses adapt to this shift and remain visible in this new search landscape.

Blueprint Digital focuses on helping brands appear not only in traditional search engine results but also in AI-generated responses across platforms like ChatGPT, Google Gemini, and Perplexity.

What Are AI SEO Services?

AI SEO go beyond standard keyword optimization. They focus on making your content accessible, relevant, and authoritative enough to be included in AI-generated answers.

This approach combines several elements, including:

• Technical optimization to ensure content is easy for AI systems to interpret
• Structured content that clearly answers user intent
• Authority building through high-quality content and backlinks
• Audience research to align with how people ask questions in AI tools

The goal is to position your brand as a trusted source that AI platforms can reference and recommend.

Why AI Search Matters

The way people search online is changing. Instead of scrolling through pages of links, users are increasingly relying on direct answers generated by AI tools.

Recent data shows that AI is already influencing a significant portion of search behavior. For example, a large percentage of users have interacted with AI tools recently, and many search queries now trigger AI-generated summaries.

This shift means businesses need to optimize not just for rankings, but for visibility within these AI responses.

A Strategic Approach to AI-Driven SEO

Effective AI SEO require a combination of strategy, content, and technical expertise. Blueprint Digital takes a comprehensive approach that aligns with how modern search works.

This typically includes:

• Identifying topics and questions your audience is asking
• Creating content that directly addresses those queries
• Structuring content for clarity and easy extraction by AI systems
• Strengthening domain authority to increase trust signals

By focusing on these areas, businesses can improve their chances of being featured in AI-driven search results.

From Visibility to Conversions

Being mentioned in AI results is valuable, but it is only part of the equation. The ultimate goal is to turn that visibility into measurable outcomes.

AI SEO is designed to:

• Increase qualified traffic
• Improve engagement with your content
• Generate leads and conversions
• Strengthen overall brand authority

By aligning SEO efforts with business goals, companies can ensure their strategy delivers real results, not just impressions.

Who Can Benefit from AI SEO?

AI-focused optimization is especially useful for businesses that rely on online visibility to generate leads or sales. This includes:

• Service-based businesses
• eCommerce brands
• B2B companies
• Local and national organizations

As AI continues to influence how people search, adopting this approach early can provide a competitive advantage.

Preparing for the Future of Search

Search is no longer limited to traditional engines. AI platforms are becoming a primary way people discover information, and businesses need to adapt accordingly.

By investing in AI SEO, companies can position themselves for long-term success in a rapidly changing digital environment. With the right strategy, it becomes possible to stay visible, relevant, and competitive as search continues to evolve.

Related: Search Engine Ranking Reports: Unveiling SEO Tools and Strategies

More four-year-olds are enrolled in state-funded preschools than ever before, but the quality and availability of preschool programs have experts concerned about creating a system of haves and have-nots.

“If providing high-quality preschool education to all 3- and 4-year-olds were a race, some states are nearing the finish line, others have stumbled and fallen behind, and a few have yet to leave the starting line,” an annual report from the National Institute of Early Education Research states.

With the amount of funding and quality varying by state, it means that access for families in states that aren’t investing still widely varies.

The report, titled “State of Preschool: 2025 Yearbook,” breaks down the annual spending, quality and enrollment numbers across early childhood education programs in the U.S. The latest found states hit an all-time high for both spending and enrollment, but the quality of the programs remains a concern.

“We’re trying to make sure states are also thinking about quality,” Allison Friedman-Krauss, an associate research professor at NIEER, says. “Right now, it’s more about access. And we don’t want them to forget about quality.”

More Funding – But Not Always More Quality

The report found funding peaked at nearly $14.4 billion, though that was largely driven by a handful of states: $4.1 billion in California alone, along with $1.2 billion in New Jersey and $1 billion in New York. Those three states accounted for nearly half (45 percent) of all state pre-K spending.

More than two dozen states also increased their preschool spending, which can go toward things like improving teacher-to-student rations and improving teacher compensation, the latter which has long been a concern.

While states still increased their spending on pre-K this year, the rate at which states are investing is slowing down. Adjusted for inflation, each state spent an average of $45 more per child than the 2023-2024 year. However, last year’s increase in spending was 16 times as large.

New Jersey, Oregon and the District of Columbia gave more than $15,000 in state funding per child enrolled in preschool. Six other states (California, Connecticut, Delaware, Michigan, New Mexico, and Washington) spent more than $10,000 per child enrolled in pre-K. Twenty eight states overall spent more funding per child, adjusted for inflation, than past years.

Seventeen states spent less on preschool in 2024-2025 than they did in 2023-2024, when adjusted for inflation. The researchers attributed the spending decline in part to overall state deficits and falling enrollment across many states.

However, that’s not always the case. New Jersey had a budget deficit but invested an additional $100 million into expanding preschool programs for all.

Pointing toward this, Steve Barnett, director of NIEER, argues that it’s all about state priorities: “That’s a conscious decision to say we’re going to spend less,” he says. “And you have to ask if the declining enrollment – even if not intentional – is a way to reduce spending [in the sector]. As opposed to, ‘Maybe we should work on getting parents to enroll their kid.’”

The boost in funding did not always correlate to better early childhood education programs. Only six states met all of NIEER’s 10 quality standards benchmarks, which includes a maximum class size of 20 students, a requirement that teachers have bachelor’s degrees and a classroom ratio of at least one staff member for every 10 students.

States looking to enhance preschool quality should focus on class size and teacher pay, Barnett argues.

Teacher pay and class sizes account for most of the money, and once states have improved those, other metrics, like curriculum supports and health screenings, are easier to pay for later, he adds.

But changes won’t happen overnight.

“It does take time. You can’t just wave a magic wand and have classroom size and teachers’ pay magically fixed,” Barnett says.

NIEER’s Friedman-Krauss, pointed to Alabama and Georgia as examples of slowly, but surely, increasing preschool quality. Georgia hit all 10 quality benchmarks this year. Friedman-Krauss credits the improvement to a $97.6 million investment by the state, which helped lower classroom size from 22 to 20 and increased teacher pay.

“We make a big deal of it because it’s serving most of the 4-year-old [children] and hitting all the benchmarks,” Barnett says. “It’s a state that lost them and came back even stronger; that’s a good sign.”

Lion’s Share of Enrollment Only in a Few States

Enrollment, similarly to funding, reached an all-time high nationally last year, with 1.8 million children during the 2024-2025 school year. But roughly half of that comes from four states: California, Texas, New York and Florida.

Notably, a dozen states had more than half of their four-year-olds in state-funded preschool programs, with the District of Columbia topping the list: 94 percent of four-year-olds were enrolled in their state programs. California’s enrollment gains were buoyed in part due to the state’s universal pre-K promise.

However, twenty states enrolled fewer preschoolers in 2024-2025 than the prior year. Some could blame the dip on declining birth rates. But when adjusted by population percentage, 21 states still saw a dip.

For some states, the enrollment decline was steep. Indeed, six states (Arizona, Florida, New York, Ohio, Oklahoma, and Wisconsin) decreased enrollment by more than 1,000 children.

Three-year-old students made up only 9 percent enrollment across the nation, up from 5 percent a decade earlier. Some states are acting to counter this. For example, Illinois and New Jersey are both focusing on expanding preschool programs for three-year-olds, Friedman-Krauss says. However, she and Barnett expect a slow mass adoption of three-year-olds in state-funded programs.

“I think there will be more attention paid to that group – how much more, that’s the hard part,” Barnett says. “Nine percent is better than when we started, but it’s very lumpy. It’s still 0 percent in lots of places.”

Carrying a Kindle Paperwhite, priced at $134.99 (was $159.99), in one’s hands everyday acts as a constant reminder of what makes this device a must-have for bookworms. This e-reader weighs only 7 oz, hence why it seems like something that the device could float as it easily fits into one’s pockets or bag without them knowing.

To kick things off, it attempts to create the real page-turning experience, and compared to a regular book, it would be like day and night difference. The new model has 300 pixels per inch, outperforming its predecessor and rendering texts as clear as a crystal in direct sunshine, making it a lifesaver for readers like myself who love to read outside. Finally, the device’s backlight works well, since it automatically adjusts based on the illumination in the room you’re reading in, and there’s even a feature that turns the brightness into a warmer color when you read late at night.

The pages flip 25% faster than in the previous version, and all menus appear instantly. It is 20% faster, which is fairly astonishing, especially for those who read books, since they will not be bored or frustrated by the time it takes to turn the pages. Also, the touch response is exceptionally fast, so it does not interfere with the reader’s perspective when reading. The battery performance provides 12 weeks of reading time for 30 minutes of reading per day without WiFi or lighting. The recharge will just take 2.5 hours.

Among other advantages, IPX8 waterproof technology ensures that you can use it even in the rain or while taking a bath without damage. Furthermore, it can withstand immersion in 2 meters of fresh water for an hour, allowing you to take it to a pool, beach, or simply bathe. In addition, the Paperwhite has a large amount of storage space; 16 GB of built-in memory allows for the storage of thousands of books. A Wi-Fi connection enables you to connect to your library in minute, or if you want to listen to an audiobook, simply turn on Bluetooth.

If you read George Orwell’s classic political satire Animal Farm in seventh grade, you probably remember the basic contours of the plot: fed up with human rule, a group of well-intentioned barnyard animals set up their own egalitarian society, with disastrous results. Published in 1945, Animal Farm has a timeless (and, certainly, contemporarily relevant) message: It’s about how the impulse to retain power will always come at the expense of our basic morality.

That message, however, seems to have been lost on most MAGA influencers assigned the book in middle school (if they even read it at all). After their failure to cancel Barbie or the Wicked movies, conservatives have moved on to a new film adaptation of Animal Farm. (The animated film, which is directed by Lord of the Rings star Andy Serkis, opens May 1).

The problem, however, is that they’ve failed to reach a consensus on what the actual message of Animal Farm is.

The right-wing outrage cycle over a movie featuring Seth Rogen making fart jokes appears to have been sparked by influencers like Emily Saves America and Riley Gaines, who recently posted the trailer for the film. In an April 28 X post, Gaines tweeted that the film was “incredibly well done. They do a perfect job of reminding viewers that Marxism always has and always will fail.” She hashtagged her tweet #AnimalFarmPartner, leading people to assume the post had been the result of a paid partnership between herself and Angel Studios, the Utah-based entertainment company distributing the film, which was also behind the faith-based blockbusters Sound of Freedom and The King of Kings.

Many on both the left and the right found Gaines’ tweet bizarre, in part because while Animal Farm is certainly a critique of Stalinism, it’s also very clearly not a full-throated endorsement of capitalist ideals. The human owner of the farm is a capitalist, and after he is overthrown, the power-hungry pigs mimic his behaviors, adopting human clothes and profiting off the labor of the other farm animals. The book is ultimately less a condemnation of specific systems of governance than a critique of mankind’s lust for power and blind adherence to ideology.

In the latest adaptation, Serkis also tweaked the plot by adding a greedy human character (voiced by Glenn Close) who wants to buy the farm, characterizing the film in USA Today as “about authoritarianism and power corrupting and our response to that”—a message that, in theory at least, would certainly resonate with 2026 audiences.

It clearly did not, however, resonate with many of Gaines’ ideological bedfellows, who pounced on her for being a Marxist shill. “Promoting communism is the new gay for pay,” right wing podcaster Tim Pool tweeted. Earlier this month, he posted that he had turned down an offer from Angel Studios to promote the film due to it being “pro communism and anti-capitalism.” The influencer Peachy Keenan also excoriated the film, calling it “retarded socialist propaganda.”

The inability to reach a consensus on the actual message of the new Animal Farm movie may very well be a reflection of its artistic merits, or lack thereof. (Indeed, the film currently has a 23 percent rating on Rotten Tomatoes.) But it’s also just generally a reflection of how little media literacy exists in our current information landscape—an issue that, in fairness, is far from specific to the right. Unless the moral messaging of a work of fiction is clearly and consistently telegraphed throughout, there seems to be a complete inability to accept ambiguity or contradiction, or to acknowledge that multiple ideas can be good or bad at the same time.

Though middle schoolers might be able to immediately grasp the takeaways from Animal Farm, it says something that high-profile political commentators can’t. In fairness, Orwell himself, who has been claimed by both the right and the left during his lifetime and beyond, probably would have appreciated the confusion his novel has wrought—even if he may not have appreciated Seth Rogen’s fart jokes.

This article is brought to you by DAIMON Robotics.

This April, Hong Kong-based DAIMON Robotics has released Daimon-Infinity, which it describes as the largest omni-modal robotic dataset for physical AI, featuring high resolution tactile sensing and spanning a wide range of tasks from folding laundry at home to manufacturing on factory assembly lines. The project is supported by collaborative efforts of partners across China and the globe, including Google DeepMind, Northwestern University, and the National University of Singapore.

The move signals a key strategic initiative for DAIMON, a two-and-a-half-year-old company known for its advanced tactile sensor hardware, most notably a monochromatic, vision-based tactile sensor that packs over 110,000 effective sensing units into a fingertip-sized module. Drawing on its high-resolution tactile sensing technology and a distributed out-of-lab collection network capable of generating millions of hours of data annually, DAIMON is building large-scale robot manipulation datasets that include vast amounts of tactile sensing data. To accelerate the real-world deployment of embodied AI, the company has also open-sourced 10,000 hours of its data.

Prof. Michael Yu Wang, co-founder and chief scientist at DAIMON Robotics, has pioneered Vision-Tactile-Language-Action (VTLA) architecture, elevating the tactile to a modality on par with vision.DAIMON Robotics

Behind the strategy is Prof. Michael Yu Wang, DAIMON’s co-founder and chief scientist. Prof. Wang earned his PhD at Carnegie Mellon — studying manipulation under Matt Mason — and went on to found the Robotics Institute at the Hong Kong University of Science and Technology. An IEEE Fellow and former Editor-in-Chief of IEEE Transactions on Automation Science and Engineering, he has spent roughly four decades in the field. His objective is to address the missing “insensitivity” of robot manipulation, which practically relies on the dominant Vision-Language-Action (VLA) model. He and his team have pioneered Vision-Tactile-Language-Action (VTLA) architecture, elevating the tactile to a modality on par with vision.

We spoke with Prof. Wang about how tactile feedback aims to change dexterous manipulation, how the dataset initiative is foreseen to improve our understanding of robotic hands in natural environments, and where — from hotels to convenience stores in China — he sees touch-enabled robots making their first real-world inroads.

Daimon-Infinity is the world’s largest omni-modal dataset for Physical AI, featuring million-hour scale multimodal data, ultra-high-res tactile feedback, data from 80+ real scenarios and 2,000+ human skills, and more.DAIMON Robotics

The Dataset Initiative

This month, DAIMON Robotics released the largest and most comprehensive robotic manipulation dataset with multiple leading academic institutions and enterprises. Why releasing the dataset now, rather than continuing to focus on product development? What impact will this have on the embodied intelligence industry?

DAIMON Robotics has been around for almost two and a half years. We have been committed to developing high-resolution, multimodal tactile sensing devices to perceive the interaction between a robot’s hand (particularly its fingertips) and objects. Our devices have become quite robust. They are now accepted and used by a large segment of users, including academic and research institutes as well as leading humanoid robotics companies.

As embodied AI continues to advance, the critical role of data has been clearer. Data scarcity remains a primary bottleneck in robot learning, particularly the lack of physical interaction data, which is essential for robots to operate effectively in the real world. Consequently, data quality, reliability, and cost have become major concerns in both research and commercial development.

This is exactly where DAIMON excels. Our vision-based tactile technology captures high-quality, multimodal tactile data. Beyond basic contact forces, it records deformation, slip and friction, material properties and surface textures — enabling a comprehensive reconstruction of physical interactions. Building on our expertise in multimodal fusion, we have developed a robust data processing pipeline that seamlessly integrates tactile feedback with vision, motion trajectories, and natural language, transforming raw inputs into training-ready dataset for machine learning models.

Recognizing the industry-wide data gap, we view large-scale data collection not only as our unique competitive advantage, but as a responsibility to the broader community.

By building and open-sourcing the dataset, we aim to provide the high-quality “fuel” needed to power embodied AI, ultimately accelerating the real-world deployment of general-purpose robotic foundation models.

The robotics industry is highly competitive, and many teams have chosen to focus on data. DAIMON is releasing a large and highly comprehensive cross-embodiment, vision-based tactile multimodal robotic manipulation dataset. How were you able to achieve this?

We have a dedicated in-house team focused on expanding our capabilities, including building hardware devices and developing our own large-scale model. Although we are a relatively small company, our core tactile sensing technology and innovative data collection paradigm enable us to build large-scale dataset.

Our approach is to broaden our offering. We have built the world’s largest distributed out-of-lab data collection network. Rather than relying on centralized data factories, this lightweight and scalable system allows data to be gathered across diverse real-world environments, enabling us to generate millions of hours of data per year.

“To drive the advancement of the entire embodied AI field, we have open-sourced 10,000 hours of the dataset for the broader community.” —Prof. Michael Yu Wang, DAIMON Robotics

This dataset is being jointly developed with several institutions worldwide. What roles did they play in its development, and how will the dataset benefit their research and products?

Besides China based teams, our partners include leading research groups from universities, such as Northwestern University and the National University of Singapore, as well as top global enterprises like Google DeepMind and China Mobile. Their decision to partner with DAIMON is a strong testament to the value of our tactile-rich dataset.

Among the companies involved there are some that have already built their own models but are now incorporating tactile information. By deploying our data collection devices across research, manufacturing and other real-world scenarios, they help us to gather highly practical, application-driven data. In turn, our partners leverage the data to train models tailored to their specific use cases. Furthermore, to drive the advancement of the entire embodied AI field, we have open-sourced 10,000 hours of the dataset for the broader community.

Equipped with Daimon’s visuotactile sensor, the gripper delicately senses contact and precisely controls force to pick up a fragile eggshell.Daimon Robotics

From VLA to VTLA: Why Tactile Sensing Changes the Equation

The mainstream paradigm in robotics is currently the Vision-Language-Action (VLA) model, but your team has proposed a Vision-Tactile-Language-Action (VTLA) model. Why is it necessary to incorporate tactile sensing? What does it enable robots to achieve, and which tasks are likely to fail without tactile feedback?

Over these years of working to make generalist robots capable of performing manipulation tasks, especially dexterous manipulation — not just power grasping or holding an object, but manipulating objects and using tools to impart forces and motion onto parts — we see these robots being used in household as well as industrial assembly settings.

It is well established that tactile information is essential for providing feedback about contact states so that robots can guide their hands and fingers to perform reliable manipulation. Without tactile sensing, robots are severely limited. They struggle to locate objects in dark environments, and without slip detection, they can easily drop fragile items like glass. Furthermore, the inability to precisely control force often leads to failed manipulation tasks or, in severe cases, physical damage. Naturally, the VLA approach needs to be enhanced to incorporate tactile information. We expanded the VLA framework to incorporate tactile data, creating the VTLA model.

An additional benefit of our tactile sensor is that it is vision-based: We capture visual images of the deformation on the fingertip surface. We capture multiple images in a time sequence that encodes contact information, from which we can infer forces and other contact states. This aligns well with the visual framework that VLA is based upon. Having tactile information in a visual image format makes it naturally suitable for integration into the VLA framework, transforming it into a VTLA system. That is the key advantage: Vision-based tactile sensors provide very high resolution at the pixel level, and this data can be incorporated into the framework, whether it is an end-to-end model or another type of architecture.

DAIMON has been known for its vision-based tactile sensors that can pack over 110,000 effective sensing units.DAIMON Robotics

The Technology: Monochromatic Vision-based Tactile Sensing

You and your team have spent many years deeply engaged in vision-based tactile sensing and have developed the world’s first monochromatic vision-based tactile sensing technology. Why did you choose this technical path?

Once we started investigating tactile sensors, we understood our needs. We wanted sensors that closely mimic what we have under our fingertip skin. Physiological studies have well documented the capabilities humans have at their fingertips — knowing what we touch, what kind of material it is, how forces are distributed, and whether it is moving into the right position as our brain controls our hands. We knew that replicating these capabilities on a robot hand’s fingertips would help considerably.

When we surveyed existing technologies, we found many types, including vision-based tactile sensors with tri-color optics and other simpler designs. We decided to integrate the best of these into an engineering-robust solution that works well without being overly complicated, keeping cost, reliability, and sensitivity within a satisfactory range, thus ultimately developing a monochromatic vision-based tactile sensing technique. This is fundamentally an engineering approach rather than a purely scientific one, since a great deal of foundational research already existed. With the growing realization of the necessity of tactile data, all of this will advance hand in hand.

DAIMON vision-based tactile sensor captures high-quality, multimodal tactile data.DAIMON Robotics

Last year, DAIMON launched a multi-dimensional, high-resolution, high-frequency vision-based tactile sensor. Compared with traditional tactile sensors, where does its core advantage lie? Which industries could it potentially transform?

The key features of our sensors are the density of distributed force measurement and the deformation we can capture over the area of a fingertip. I believe we have the highest density in terms of sensing units. That is one very important metric. The other is dynamics: the frequency and bandwidth — how quickly we can detect force changes, transmit signals, and process them in real time. Other important aspects are largely engineering-related, such as reliability, drift, durability of the soft surface, and resistance to interference from magnetic, optical, or environmental factors.

A growing number of researchers and companies are recognizing the importance of tactile sensing and adopting our technology. I believe the advances in tactile sensing will elevate the entire community and industry to a higher level. One of our potential customers is deploying humanoid robots in a small convenience store, with densely packed shelves where shelf space is at a premium. The robot needs to reach into very tight spaces — tighter than books on a shelf — to pick out an object. Current two-jaw parallel grippers cannot fit into most of these spaces. Observing how humans pick up objects, you clearly need at least three slim fingers to touch and roll the object toward you and secure it. Thus, we are starting to see very specific needs where tactile sensing capabilities are essential.

From Academia to Startup

After 40 years in academia — founding the HKUST Robotics Institute, earning prestigious honors including IEEE Fellow, and serving as Editor-in-Chief of IEEE TASE — what motivated you to found DAIMON Robotics?

I have come a long way. I started learning robotics during my PhD at Carnegie Mellon, where there were truly remarkable groups working on locomotion under Marc Raibert, who founded Boston Dynamics, and on manipulation under my advisor, Matt Mason, a leader in the field. We have been working on dexterous manipulation, not only at Carnegie Mellon, but globally for many years.

However, progress has been limited for a long time, especially in building dexterous hands and making them work. Only recently have locomotion robots truly taken off, and only in the last few years have we begun to see major advancements in robot hands. There is clearly room for advancing manipulation capabilities, which would enable robots to do work like humans. While at Hong Kong University of Science and Technology, I saw increasingly greater people entering this area in the form of students and postdoctoral researchers. We wanted to jumpstart our effort by leveraging the available capital and talent resources.

Fortunately, one of my postdocs, Dr. Duan Jianghua, has a strong sense for commercial opportunities. Recognizing the rapid growth of robotics market and the unique value that our vision-based tactile sensing technology could bring, together we started DAIMON Robotics, and it has progressed well. The community has grown tremendously in China, Japan, Korea, the U.S., and Europe.

Robots equipped with DAIMON technology have been deployed in factory settings. The company aims to enable robots to achieve “embodied intelligence” and close the gap between what they can see and what they can feel.DAIMON Robotics

Business Model and Commercial Strategy

What is DAIMON’s current business model and strategic focus? What role does the dataset release play in your commercial strategy?

We started as a device company focused on making highly capable tactile sensors, especially for robot hands. But as technology and business developed, everyone realized it is not just about one component, rather the entire technology chain: devices, data of adequate quality and quantity, and finally the right framework to build, train, and deploy models on robots in real application environments.

Our business strategy is best described as “3D”: Devices, Data, and Deployment. We build devices for data collection, our own ecosystem, and for deploying them in our partners’ potential application domains. This enables the collection of real-world tactile-rich data and complete closed-loop validation. This will become an integral part of the 3D business model. Most startups in this space are following a similar path until eventually some may become more specialized or more tightly integrated with other companies. For now, it is mostly vertical integration.