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We Need to Rethink the ‘A’ in AI

Parker Lennox
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We Need to Rethink the ‘A’ in AI

The AI Paradox: How Our Attitudes to Technology are Evolving

The Rise of AI in Our Lives

This month, artificial intelligence bots have slid into Santa’s grotto. For one thing, AI-enabled gifts are proliferating — as I know myself, having just been given an impressive AI-dictation device. Meanwhile, retailers such as Walmart are offering AI tools to provide frazzled shoppers with holiday help. These AI tools seem to work quite well, judging from recent reviews.

The Paradox of AI: Benefits and Fears

However, here is the paradox: even as AI spreads into our lives, hostility remains sky-high. Earlier this month, a British government survey found that four out of ten people expect AI to deliver benefits. However, three out of ten anticipate significant harm, due to "data security" breaches, "the spread of misinformation" and "job displacement."

Rethinking AI: From "Artificial" to "Augmented" Intelligence

That is no surprise, perhaps. The risks are real and well-advertised. However, as we move into 2025, it is worth pondering three oft-ignored points about the current anthropology of AI that might help to frame this paradox in a more constructive way.

First, we need to rethink which "A" we are using in "AI" today. Yes, machine learning systems are "artificial". However, bots are not always — or not usually — replacing our human brains, as an alternative to flesh-and-blood cognition. Instead, they usually enable us to operate faster and move more effectively through tasks. Shopping is just one case in point. Perhaps we should reframe AI as "augmented" or "accelerated" intelligence — or else "agentic" intelligence, to use the buzzword for what a recent Nvidia blog calls the "next frontier" of AI. This refers to bots that can act as autonomous agents, performing tasks for humans at their command.

The Cultural Frame of AI

Second, we need to think beyond Silicon Valley’s cultural frame. Until now, "anglophone actors" have "dominated the debate" around AI on the world stage, as the academics Stephen Cave and Kanta Dihal note in the introduction to their book, Imagining AI. That reflects US tech dominance. However, other cultures view AI slightly differently. Attitudes in developing countries, say, tend to be far more positive than in developed ones, as James Manyika, co-head of a UN advisory body on AI, and senior Google official, recently told Chatham House.

The Japanese Perspective on AI

Countries such as Japan are different too. Most notably, the Japanese public has long displayed far more positive sentiments towards robots than their anglophone counterparts. And this is now reflected in attitudes around AI systems too. One factor is Japan’s labour shortage (and the fact that many Japanese are wary of having immigrants plug this gap, thus finding it easier to accept robots). Another is popular culture. In the second half of the 20th century, when Hollywood films such as The Terminator or 2001: A Space Odyssey were spreading fear of intelligent machines in anglophone audiences, the Japanese public was mesmerized by the Astro Boy saga, which depicted robots in a benign light.

Conclusion

As we move into 2025, it is clear that our attitudes towards AI will keep subtly shifting as the technology becomes increasingly normalised. That may alarm some, but it may also help us to reframe the tech debate more constructively, and to focus on ensuring that humans control their digital "agents" — not the other way round. Investors today might be dashing into AI, but they need to ask what "A" they want in that AI tag.

FAQs

Q: What is the current state of AI adoption?
A: AI-enabled gifts are proliferating, and retailers are offering AI tools to provide shopping and gifting shortcuts.

Q: What are the concerns around AI?
A: Three out of ten people anticipate significant harm from AI, citing data security breaches, misinformation, and job displacement.

Q: How do different cultures view AI?
A: Attitudes towards AI vary across cultures, with developing countries tend to be more positive, and Japan displaying a more positive sentiment towards robots.

Q: What is the future of AI?
A: As AI becomes increasingly normalised, our attitudes will continue to shift, and it is crucial to focus on ensuring humans control their digital "agents" — not the other way round.

Mastering Materials in KeyShot

Phil
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0
Mastering Materials in KeyShot

Working with Materials in KeyShot

One of the best things about KeyShot is its ability to create and render realistic materials. When paired with beautiful lighting, product visualisations take on a whole new level of believability. When it comes to materials, KeyShot isn’t quite as advanced as some other rendering packages, but that doesn’t mean it isn’t still able to create some killer materials.

01. Use the Materials panel

The Materials panel is where you can find a full library of various materials from plastics to metals and glass to stone. Applying these to parts of your model is as simple as dragging and dropping them either into the viewport or into the Scene panel object hierarchy.

(Image: © Paul Hatton)

02. Copy and Paste Materials

One of my favourite features is the Copy and Paste Material options. This lets you take one material from a component and paste it onto another. This is a big time saver and as easy as right-clicking on a component in the viewport and selecting Copy Material before selecting another, right-clicking, and selecting Paste Material.

(Image: © Paul Hatton)

03. Material Properties

If the range of materials aren’t customised enough for your needs, you can head to the Material properties panel to make finer adjustments. Select a material by either double-clicking it in the viewport or the list of thumbnails. Changing its Properties type using the dropdown adjusts the base properties of the material, but you can also adjust the Diffuse, Specular and Roughness properties. All adjustments are replicated in real time in the viewport, so you can play around with the options and see how each impacts the end result.

(Image: © Paul Hatton)

04. Textures and Labels

The Textures tab in the Properties panel brings up a world of functionality. You can add any texture map across Diffuse, Specular, Bump and Opacity channels. These can also be mapped with any mapping type or even adjusted in the Size and Mapping rollout. If your model has already been UV-mapped, that will be transferred through. You can also apply decals in the Labels tab.

(Image: © Paul Hatton)

Conclusion

KeyShot offers a wide range of materials and tools to help you create realistic and believable product visualisations. By using the Materials panel, Copy and Paste Materials, Material Properties, and Textures and Labels, you can create stunning materials that will take your product visualisations to the next level.

FAQs

Q: What is the best way to apply materials to multiple components in KeyShot?
A: The best way to apply materials to multiple components in KeyShot is to join components together into the same mesh, group components by material, or use the Link Materials functionality.

Q: How do I adjust the properties of a material in KeyShot?
A: You can adjust the properties of a material in KeyShot by selecting the material and using the Material properties panel. You can also adjust the Diffuse, Specular and Roughness properties.

Q: Can I add textures to a material in KeyShot?
A: Yes, you can add textures to a material in KeyShot by using the Textures tab in the Properties panel. You can add any texture map across Diffuse, Specular, Bump and Opacity channels.

AI Data Centers Growing ‘Mind-Blowingly Large’

Emerson Blake
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AI Data Centers Growing ‘Mind-Blowingly Large’

Data Centers Grow to Unprecedented Sizes to Support Artificial Intelligence

Large data centers are getting enormous, with some spanning over two kilometers, according to Gary Smith, CEO of Ciena, a company that makes fiber-optic networking equipment used by cloud computing vendors to connect their data centers.

Enormous Data Centers

"These campuses are getting bigger and longer," Smith said in an interview with The Technology Letter. "The campus, which comprises many buildings, is blurring the line between what used to be a wide-area network and what’s inside the data center."

Strain on Direct-Connect Technology

The increasing size of these campuses is putting massive strain on direct-connect technology, which is used to connect GPUs inside the data center. Smith expects to start selling fiber-optic equipment in coming years that is similar to what is in long-haul telecom networks but tweaked to connect GPUs inside the data center.

Fiber-Optic Equipment

A direct-connect device is a networking device that is purpose-built to let GPUs talk to one other, such as Nvidia’s "NVLink" networking products. Smith’s remarks echo comments by others serving the AI industry, such as Thomas Graham, co-founder of chip startup Lightmatter, who said at a Bloomberg Intelligence conference that there are at least a dozen new AI data centers planned or in construction now that require a gigawatt of power to run.

Power Requirements

"Just for context, New York City pulls five gigawatts of power on an average day, so, multiple NYCs," Graham said. By 2026, it’s expected the world’s AI processing will require 40 gigawatts of power "specifically for AI data centers, so eight NYCs."

Conclusion

As data centers continue to grow to support the increasing demands of artificial intelligence, the need for advanced networking technology is becoming more pressing. The strain on direct-connect technology is a clear indication of the need for innovative solutions to connect GPUs inside these massive data centers.

Frequently Asked Questions

Q: What is the size of some of these large data centers?
A: Some of these data centers are over two kilometers long, equivalent to over 1.24 miles.

Q: What is the impact on direct-connect technology?
A: The increasing size of these campuses is putting massive strain on direct-connect technology, which is used to connect GPUs inside the data centers.

Q: What is Ciena’s solution to this problem?
A: Ciena is working on developing fiber-optic equipment similar to what is used in long-haul telecom networks but tweaked to connect GPUs inside the data center.

X’s Blue Checkmarks Still Causing Chaos

Phil
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X’s Blue Checkmarks Still Causing Chaos

The Ongoing Chaos of Twitter’s "Lords & Peasants" System

Two years ago, Elon Musk launched ‘Twitter Blue’ with a ghastly logo design and a promise to end Twitter’s "lords & peasants system" by offering blue checkmarks to anyone prepared to pay $8 a month. Coming before the rebrand to X, the move almost killed the platform, and things haven’t got much better.

The Rise of Parody Accounts

With so many parody accounts buying ‘verified’ status, Twitter had to add first grey and then gold checkmarks. The result was a system of lords, peasants, and peasants who paid to not look like peasants but whose shiny blue tick was now worthless.

The Current State of X Premium

Two years on, things are no less chaotic, with some paying peasants now complaining that their paid-for blue checkmarks are being taken away. Twitter Blue is no more, replaced with X Premium, which has been trying to promote itself as the ideal Christmas gift (perhaps for someone you really hate). But it seems that paying for a blue tick doesn’t mean it’s yours to keep.

The Controversy Unfolds

There’s been a spate of complaints from people saying they had their checkmarks removed or placed ‘under review’ despite paying for X Premium. Some are claiming that it’s an attempt by Musk to stifle criticism or the expression of political views that he disagrees with, but strangely many of the people complaining are as extreme right as Musk if not more so.

Payment Complications and Censorship

It seems the mass blue tick outage may have a more mundane explanation related to payment complications involving ConservativeOG, to which many of the people complaining are linked. But Musk has caused even more controversy by revealing that verified users have the power to lower the reach of other users’ accounts by muting them. So much for an end to "lords and peasants".

The Unreliability of X

The latest controversy shows why advertisers won’t touch X. The platform has become so unreliable and prone to random chaos.

Conclusion

The ongoing chaos of Twitter’s "lords & peasants" system is a testament to the platform’s inability to deliver on its promises. With payment complications, censorship, and controversy, it’s no wonder that X is struggling to attract and retain users.

FAQs

Q: What is X Premium?
A: X Premium is the rebranded version of Twitter Blue, offering blue checkmarks to those who pay $8 a month.

Q: Why are people complaining about their paid-for blue checkmarks being taken away?
A: Some people are claiming that their checkmarks were removed or placed ‘under review’ despite paying for X Premium, and are accusing Musk of trying to stifle criticism or political views.

Q: What is the recent controversy about?
A: The recent controversy revolves around payment complications and censorship, with verified users having the power to lower the reach of other users’ accounts by muting them.

Q: Why is X struggling to attract and retain users?
A: X is struggling due to its unreliability, prone to random chaos, and controversies surrounding payment complications and censorship.

Pronouncing the “Gif”

Phil
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0
Pronouncing the “Gif”

Live Stream: AINews

Introduction
The AINews team is excited to announce that we are now live on YouTube! Join us as we share our latest updates, insights, and behind-the-scenes stories.

What to Expect

  • Live Q&A session with our team
  • Exclusive updates on upcoming projects and initiatives
  • Behind-the-scenes stories from our team
  • Fun and engaging content for our community

The Livestream
Watch the livestream here: https://www.youtube.com/watch?v=ANdPTXbNUa0

Follow Us

Follow me on X: https://x.com/mreflow

Conclusion
We are thrilled to share this experience with you and can’t wait to see you on our livestream!

Frequently Asked Questions

Q: What is the purpose of this livestream?
A: This livestream is to share our latest updates, behind-the-scenes stories, and Q&A session with our community.

Q: How do I watch the livestream?
A: You can watch the livestream on our YouTube channel: https://www.youtube.com/watch?v=ANdPTXbNUa0

Q: How do I follow you on X?
A: You can follow me on X by clicking this link: https://x.com/mreflow

Q: What kind of content can I expect to see during the livestream?
A: You can expect to see exclusive updates on upcoming projects, behind-the-scenes stories, and fun and engaging content for our community.

Big O: The Secret to Speedy Code

Parker Lennox
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0
Big O: The Secret to Speedy Code

What is Big O Anyway?

Imagine you’re at a fancy dinner party, and everyone’s talking about something incredibly sophisticated—like quantum mechanics or the latest Doctor Who episode. You know just enough to nod along and look intelligent, but deep down, you have no idea what’s going on. That’s how I felt when I first encountered Big O notation.

But fear not, my friend! Big O is not here to make you feel like a clueless guest at a party. It’s actually a way of measuring how fast or slow an algorithm is. It’s like looking at a recipe—Big O is the measure of how long it’ll take to make that cake, regardless of whether your oven is brand new or straight out of the 90s.

Why Do We Care About Big O?

Alright, so you’ve got a killer algorithm that solves problems like a pro, but here’s the catch: Does it solve them quickly enough? Big O helps you figure out if your algorithm is going to turn into a sluggish sloth or if it’s going to take off like the Flash. 🚀

Think about it: You could write a code that solves a problem, but if it takes forever to run, it’s pretty much useless in the real world (unless you’re trying to simulate the aging process of a tortoise—then, it’s perfect).

Breaking Down Big O Notation: Let’s Get Personal

Here’s the thing: Big O notation isn’t about the exact time an algorithm will take. It’s about the rate at which the algorithm’s runtime grows as the input size increases. Think of it as trying to eat a bowl of spaghetti (stay with me here) as the noodles keep multiplying. The more noodles there are, the longer it’ll take you to finish. Simple, right?

Here are the common Big O “personalities” you’ll meet along the way:

O(1) — The Fast and the Furious

This is your fast lane—the Vin Diesel of Big O. It doesn’t matter how big the input gets; the time it takes to run your code stays the same. You could double the number of noodles in that spaghetti bowl, and O(1) still won’t break a sweat. It’s like showing up to the party and knowing you’re the fastest one there, no traffic jams, no slow walkers.

Example: Accessing a value in a list by index.

O(n) — The Casual Walk in the Park

O(n) is the friend who doesn’t rush, but still gets where they need to go eventually. As the input grows, the time taken grows at the same rate. Double the number of noodles, and it’s going to take you twice as long to eat them.

Example: Looping through an array to find a specific element.

O(n²) — The Social Butterfly (Too Many Friends)

Imagine you’re trying to make a list of every possible pair of friends at a party. You’d have to compare every guest with every other guest—sounds like a lot, right? O(n²) takes the longest because it grows exponentially as the input increases. If there are 100 guests at the party, you’re making 10,000 comparisons. Yikes!

Example: Nested loops, like checking all pairs in a 2D array.

O(log n) — The Cool and Collected Binary Search

O(log n) is that person who takes the shortest path to the finish line, like someone using Google Maps to avoid traffic. They don’t need to explore the entire space. Instead, they cut the search area in half with each step. It’s efficient, like searching for a word in the dictionary—you don’t start from A and check every single word, you jump to a spot and keep narrowing it down.

Example: Binary Search.

Big O in the Real World: Why It Matters

Now that you’ve met the Big O family, you might be wondering, “Why does this matter to me?” Well, let’s think back to our traffic jam analogy. Imagine you’re trying to write code for a large system with thousands or millions of users. If your code has O(n²) behavior, it’s like trying to navigate a 20-lane highway during rush hour. Things are going to slow down, and your users will notice. But if you’re using O(log n), you’re that savvy driver who knows all the shortcuts and keeps everything running smoothly.

Wrapping Up: A Speedy Code, a Happy Life

Big O isn’t just a bunch of abstract math that lives in the depths of computer science books. It’s practical, and knowing how to optimize your algorithms can make a huge difference in how quickly your code runs, especially when it’s dealing with massive amounts of data.

So the next time you’re faced with a problem to solve, remember: Choose your algorithm like you’d choose a fast, reliable route to the airport. Avoid the traffic jams (i.e., avoid those O(n²) nested loops), and you’ll find yourself in the fast lane to success.

And hey, if you ever get lost in the world of Big O again, just think of it as navigating through traffic—only this time, you’ve got the perfect GPS to guide you.

Happy coding, speedsters! 🚗💨

FAQs

Q: What is Big O notation?

A: Big O notation is a way of measuring how fast or slow an algorithm is. It’s like looking at a recipe—Big O is the measure of how long it’ll take to make that cake, regardless of whether your oven is brand new or straight out of the 90s.

Q: Why is Big O important?

A: Big O is important because it helps you figure out if your algorithm is going to be fast or slow. It’s like considering the traffic jam analogy—you want to avoid the slow traffic (O(n²)) and choose the fast route (O(log n)).

Q: What are the common Big O “personalities”?

A: The common Big O “personalities” are O(1), O(n), O(n²), and O(log n). Each personality represents a different rate at which the algorithm’s runtime grows as the input size increases.

Q: How do I apply Big O in real-world scenarios?

A: You can apply Big O in real-world scenarios by considering the input size and choosing an algorithm that’s efficient. For example, if you’re dealing with a large dataset, you might choose an O(log n) algorithm to speed up the process.

Top 5 AI Podcast Episodes of 2024

Emerson Blake
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Top 5 AI Podcast Episodes of 2024

NVIDIA’s AI Podcast: Top Episodes of 2024

The Inside Scoop on AI’s Transformative Power

NVIDIA’s AI Podcast has been giving listeners the inside scoop on the ways AI is transforming nearly every industry since its debut in 2016. With over 6 million listens across 200-plus episodes, the podcast has covered a wide range of topics, from generative AI-powered applications to the latest advancements in AI research.

Top Episodes of 2024

  1. AI and Sustainability

Joshua Parker, senior director of corporate sustainability at NVIDIA, discusses how AI and accelerated computing are contributing to a more sustainable future by improving energy efficiency and helping address climate challenges.

[iframe src="https://w.soundcloud.com/player/?url=https%3A//api.soundcloud.com/tracks/1940222278&color=%2376b900&auto_play=false&hide_related=false&show_comments=true&show_user=true&show_reposts=false&show_teaser=true" width="100%" height="166" frameborder="no" scrolling="no"]

  1. Reshaping Productivity with AI

Xuedong Huang, CTO of Zoom, shares how the company is reshaping productivity with AI, playing a pivotal role for many during the COVID-19 pandemic.

[iframe src="https://w.soundcloud.com/player/?url=https%3A//api.soundcloud.com/tracks/1746649332&color=%2376b900&auto_play=false&hide_related=false&show_comments=true&show_user=true&show_reposts=false&show_teaser=true" width="100%" height="166" frameborder="no" scrolling="no"]

  1. Empowering Computational Services

Alan Chalker, director of strategic programs at the Ohio Supercomputer Center, shares how the center empowers Ohio higher education institutions and industries with accessible, reliable, and secure computational services, and works with client companies like NASCAR, which is simulating race car designs virtually.

[iframe src="https://w.soundcloud.com/player/?url=https%3A//api.soundcloud.com/tracks/1759544883&color=%2376b900&auto_play=false&hide_related=false&show_comments=true&show_user=true&show_reposts=false&show_teaser=true" width="100%" height="166" frameborder="no" scrolling="no"]

  1. Generative AI for Content Creation

Pinar Seyhan Demirdag, cofounder and CEO of Cuebric, discusses how the company’s AI-powered application makes high-quality production more accessible and affordable, helping anyone become a content creator by rapidly bringing ideas to life.

[iframe src="https://w.soundcloud.com/player/?url=https%3A//api.soundcloud.com/tracks/1731441726&color=%2376b900&auto_play=false&hide_related=false&show_comments=true&show_user=true&show_reposts=false&show_teaser=true" width="100%" height="166" frameborder="no" scrolling="no"]

  1. AI-Powered Solution for Heart Disease Detection

Dr. Keith Channon, cofounder and chief medical officer at health tech startup Caristo Diagnostics, discusses an AI-powered solution for detecting coronary inflammation — a key indicator of heart disease — in cardiac CT scans, which could help physicians improve treatment plans and risk predictions.

[iframe src="https://w.soundcloud.com/player/?url=https%3A//api.soundcloud.com/tracks/1924472510&color=%2376b900&auto_play=false&hide_related=false&show_comments=true&show_user=true&show_reposts=false&show_teaser=true" width="100%" height="166" frameborder="no" scrolling="no"]

Subscribe to the AI Podcast

Get the AI Podcast through Amazon Music, Apple Podcasts, Google Podcasts, Google Play, Castbox, DoggCatcher, Overcast, PlayerFM, Pocket Casts, Podbay, PodBean, PodCruncher, PodKicker, SoundCloud, Spotify, Stitcher, and TuneIn.

Conclusion

NVIDIA’s AI Podcast has once again showcased the transformative power of AI in various industries, from sustainability to content creation. The podcast has consistently provided valuable insights and expert opinions on the latest advancements in AI research and applications.

Frequently Asked Questions

Q: What is the AI Podcast about?
A: The AI Podcast is a series of episodes that explore the latest advancements in AI research and applications across various industries.

Q: How many episodes has the AI Podcast had so far?
A: The AI Podcast has had over 200 episodes since its debut in 2016.

Q: Can I subscribe to the AI Podcast?
A: Yes, you can subscribe to the AI Podcast through various podcast platforms, including Amazon Music, Apple Podcasts, Google Podcasts, and more.

OpenAI Announces Plan to Transform into a For-Profit Company

Avery Winslow
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0
OpenAI Announces Plan to Transform into a For-Profit Company

OpenAI Plans to Become a For-Profit Company

New Structure to Allow for Greater Capital Raising

OpenAI has laid out plans to become a for-profit company, with a new structure that will put control in the hands of its for-profit arm. The company’s board announced the change in a blog post, stating that it will replace its existing structure with one that operates as a Public Benefit Corporation (PBC).

What Does This Mean for OpenAI?

Going into 2025, OpenAI plans to become a PBC, which is a for-profit company designed to operate for the good of society. The PBC will run and control OpenAI’s operations and business, while OpenAI’s nonprofit will retain a stake in the business but lose its oversight role.

Nonprofit to Focus on Charitable Initiatives

The nonprofit will operate separately with its own leadership team and staff to pursue charitable initiatives in sectors such as healthcare, education, and science. This structure will allow OpenAI to raise the necessary capital to build towards artificial general intelligence while creating one of the best-resourced non-profits in history.

Raising Capital

The hundreds of billions of dollars that major companies are now investing in AI development show what it will take for OpenAI to continue pursuing its mission. The company needs to raise more capital than initially imagined, and investors want to back it, but at this scale of capital, they need conventional equity and less structural complexity.

Structure of the New Company

Under the structure outlined by OpenAI’s board, the nonprofit will get shares in the PBC at a fair valuation determined by independent financial advisors. This change has raised concerns about keeping OpenAI’s nonprofit board in control, which was a major issue last year when its members ousted CEO Sam Altman but later reinstated him.

FAQs

Q: What does this mean for OpenAI’s mission?

A: This change will allow OpenAI to raise the necessary capital to build towards artificial general intelligence while creating one of the best-resourced non-profits in history.

Q: How will the nonprofit be structured?

A: The nonprofit will operate separately with its own leadership team and staff to pursue charitable initiatives in sectors such as healthcare, education, and science.

Q: What is a Public Benefit Corporation (PBC)?

A: A PBC is a for-profit company designed to operate for the good of society. The PBC will run and control OpenAI’s operations and business, while OpenAI’s nonprofit will retain a stake in the business but lose its oversight role.

Pensive Portrait of a Soldier of the Future

Phil
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0
Pensive Portrait of a Soldier of the Future

Popularity_Choi’s 3D Art of the Week: Spine Jetpacker

Artist’s Insights

Popularity_Choi, a 3D character artist from Pangyo in South Korea, has created an impressive piece called Spine Jetpacker. This futuristic soldier is based on concept art by Yintion J – Jiang Geping. Choi used a range of software to bring this character to life, including 3ds Max, ZBrush, Substance 3D Painter, UVLayout, TopoGun, Marvelous Designer, FiberShop, Marmoset Toolbag, and Photoshop.

The Creation Process

For the mechanical parts, Choi first sketched in ZBrush using DynaMesh, referring to Keos Masons’ hard-surface techniques. He then separated each part, retopologised them, and refined the details.

Texturing and Details

The modern military-style clothing needed realistic folds, so Choi created it using Marvelous Designer. The most enjoyable part of this project was the texturing. Choi had fun working on it because there were many objects with various decals engraved.

Easter Eggs

As an additional Easter egg, Choi also wrote the names of his favorite singers and songs on the wings. He’d like to thank Lim Jaegil for mentoring him during the project.

Conclusion

Spine Jetpacker is an impressive piece of 3D art that showcases Choi’s skills in creating detailed and realistic characters. The use of various software and techniques has resulted in a stunning model that is sure to inspire other artists.

FAQs

Q: What software did Popularity_Choi use to create Spine Jetpacker?
A: Choi used 3ds Max, ZBrush, Substance 3D Painter, UVLayout, TopoGun, Marvelous Designer, FiberShop, Marmoset Toolbag, and Photoshop.

Q: What was the most challenging part of this project?
A: Choi mentioned that creating the mechanical parts was quite a challenge for him, as he is used to creating characters for medieval fantasy concepts.

Q: What was the most enjoyable part of this project?
A: Choi enjoyed the texturing process, as there were many objects with various decals engraved.

Q: Are there any Easter eggs in the model?
A: Yes, Choi wrote the names of his favorite singers and songs on the wings as an additional Easter egg.

Need a new laptop for the new year?

Phil
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0
Need a new laptop for the new year?

The Best Amazon After-Christmas Sale Laptop Deals

US Deals

Right now, you can save $150 on this year’s M3 MacBook Air with 16GB of memory. This laptop is perfect for general home use, and its sleek design and long battery life make it a great choice for everyday tasks.

Apple MacBook Air M3 (16GB, 256GB SSD)

* Original price: $1,299
* Discount: $150
* New price: $1,149

UK Deals

If you’re looking for a more powerful laptop, the Asus Vivobook Pro with Nvidia graphics is a great option. You can save up to $500 on this device, making it an excellent choice for gaming and content creation.

Asus Vivobook Pro (16GB, 512GB SSD, Nvidia GeForce GTX 1650 Ti)

* Original price: $1,499
* Discount: $500
* New price: $999

I’ve picked through the Amazon Winter Sale to seek out after-Christmas sale laptop deals in both the US and UK, looking for devices that will suit different needs, from general home use to gaming and content creation. These are the best deals going today, but also check our guide to the best laptops for video editing and the best laptop for graphic design.

Conclusion

If you’re due for a new laptop, now’s the perfect time to upgrade. With these discounted prices, you can get a high-performance device without breaking the bank. Make sure to check the deals above and grab your new laptop before they’re gone!

FAQs

Q: What is the deadline for these deals?

A: The deals are valid until the end of the Amazon Winter Sale, which is on [insert date].

Q: Are these prices limited to Amazon Prime members?

A: No, these deals are open to all Amazon customers.

Q: Can I get free shipping with these deals?

A: Yes, all of these deals include free standard shipping.

Q: Are there any other discounts available?

A: Yes, check our guide to the best laptops for video editing and the best laptop for graphic design for more deals and discounts.

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