TL;DR – What You Need to Know in 30 Seconds

• Perplexity’s Deep Research tool offers advanced AI research capabilities for a fraction of typical enterprise costs.
• It provides five free queries daily and charges $20 per month for 500 queries—compared to big AI providers charging thousands.
• Scored 93.9% on SimpleQA and 20.5% on Humanity’s Last Exam, outpacing Google’s Gemini Thinking, with OpenAI only slightly higher at 26.6%.
• Enterprise AI spending is projected to rise by 5.7% in 2025, although some companies are increasing their AI budget by 10% or more.Deep Research could shift the market by making companies question premium AI subscriptions that cost up to 100x more.
• The tool handles a range of tasks (healthcare, finance, market research) in under three minutes, democratising AI for smaller businesses and individuals.
• This affirms a new era in AI, where affordability meets performance, and big spenders must now justify their exorbitant costs.

Unpacking Perplexity Deep Research Tool, and its Impact

Today, we’re diving into one of the most talked-about innovations in AI right now: Perplexity’s new Deep Research tool. If you haven’t heard of it yet, don’t fret—this is precisely what we’re here for. Grab your favourite cuppa, because we’re about to explore how Perplexity is turning AI research upside down, smashing cost barriers, and making us question every pricey AI subscription that’s ever crossed our desks. Sound good? Let’s get stuck in!

The Big Bang of Affordable AI

You know how some products come along and make you wonder why you ever paid so much for something else? That’s exactly what’s happening with Perplexity’s Deep Research. In a single, bold move, Perplexity has basically told the rest of the AI industry: “We’re here, we’re cheap, and we’re not messing about.” If you haven’t caught wind of it, Deep Research is a tool that can generate comprehensive research reports in just minutes. Yes, minutes. And here’s the kicker: it offers advanced AI capabilities at a fraction of the typical enterprise costs.

Take a look at what’s on the table: while Anthropic and OpenAI can easily charge into the thousands every month for their premium services, Perplexity is throwing in five free queries daily for all users and an upgrade at $20 per month for 500 daily queries plus faster processing speeds. That’s not just cheaper; it’s borderline scandalous when you see that other AI giants charge almost 100 times more for near-similar (and, in some cases, arguably lesser) capabilities.

But it’s not just a marketing gimmick. Aravind Srinivas, Perplexity’s CEO, shared the company’s ethos on X (formerly Twitter), saying, “Knowledge should be universally accessible and useful. Not kept behind obscenely expensive subscription plans that benefit the corporates, not in the interests of humanity!” It’s hard not to be inspired by that. The democratisation of AI has long been touted as the Next Big Thing in tech, but Perplexity is making some serious strides to actually achieve it, rather than just talk about it.

Deep Research is now a commodity thanks to Perplexity pic.twitter.com/Fk8yvPTLzV— Aravind Srinivas (@AravSrinivas) February 14, 2025

Enterprise AI Spending Under the Microscope

As you might guess, this sudden plunge in price is raising eyebrows—big time. Large enterprises have been funnelling massive budgets into AI, with some expecting to increase their AI spending by 5.7% in 2025. That’s despite overall IT budgets going up by less than 2%. In certain sectors, that surge in AI spending could be as high as 10%, and on average, some businesses plan to throw in an additional $3.4 million into AI initiatives. With the rise of Deep Research, though, those expensive subscriptions now look a little, well, questionable.

Let’s be real. When you’ve got a brand-new AI tool that gives near-enterprise level performance (and sometimes even more advanced capabilities) for $20 a month, it begs the question: What are we actually paying for with those premium AI subscriptions? If you’re on the corporate side, you might be reviewing your budgets as we speak. Think about the training, the data hosting, the staff overhead—yes, those are real costs. But are they enough to justify a 100x difference in price?

Technical Mastery That’s Giving Giants a Run for Their Money

Now, let’s talk numbers, because who doesn’t love a good metric? Perplexity’s Deep Research scored a whopping 93.9% accuracy on the SimpleQA benchmark and clocked 20.5% on Humanity’s Last Exam. If you’re wondering why that second number is interesting, consider that it outperforms Google’s Gemini Thinking and other top-tier models. Even more eyebrow-raising is that OpenAI scores 26.6% on Humanity’s Last Exam—yes, that’s higher than Perplexity’s 20.5%—but let’s not forget the monstrous cost difference for that extra 6 percentage points.

Perplexity also claims that Deep Research completes most tasks in under three minutes, performing dozens of searches and analysing hundreds of sources simultaneously. That’s lightning-fast by any measure, especially when you realise it’s essentially replicating what expert human researchers would do—but in a fraction of the time. For advanced tasks like financial analysis, market research, technical documentation, or even healthcare insights, it’s an absolute game-changer.

Why This Matters to You (and Everyone Else)

Alright, it’s cheap, it’s fast, and it’s accurate. Who cares, right? Well, pretty much anyone who’s ever wanted to make use of advanced AI capabilities but balked at the price tag. It’s no secret that enterprise AI has often ended up creating a digital divide: if you’ve got the budget, you can do some serious data-crunching, but if not, you’re left in the dark ages. This means smaller businesses, individual researchers, students, or freelancers could only dream of some of these AI services because they couldn’t justify the cost.

But along comes Perplexity, democratising the whole playing field. The potential is enormous. If you’re a small tech start-up, you no longer have to pay thousands just to get your data insights. Researchers can use Deep Research for thorough academic or industry analyses. Professionals in healthcare or finance can produce detailed reports that would usually cost an arm and a leg. And because Perplexity plans to expand Deep Research to iOS, Android, and Mac platforms, access is only going to get easier.

Is Enterprise AI in for a Shake-up?

If you’re in charge of procurement or strategic decisions for a big firm, your job just got a bit more complicated. Do you stick with the big-name provider with that hefty subscription fee, or do you try Perplexity to see if it meets your organisation’s needs? The key question is: Are you really getting the added value for your money when your monthly AI bills are in the thousands?

Sure, there could be a few reasons to keep paying extra. Perhaps you’re already deeply integrated with a certain AI ecosystem, or you need custom solutions that only a big player can provide. Maybe you rely on dedicated customer support that’s included with your pricy subscription. But the argument that premium cost automatically translates to premium capability is quickly losing steam.

With Perplexity’s impressive performance, we might see a future where expensive enterprise AI tools have to scramble to prove they’re worth it. You can’t just plaster “enterprise-grade” on a service and watch the money roll in—users want tangible, cost-effective results.

How Deep Research Outperforms (and Where It May Still Lag)

Let’s not gloss over the fact that OpenAI’s own research capabilities still technically inch out ahead in certain benchmarks. A 26.6% score on Humanity’s Last Exam compared to Perplexity’s 20.5% might be a big deal for mission-critical tasks in specialised domains. Then again, Perplexity’s 93.9% on SimpleQA is hardly peanuts. And let’s remember the price difference—OpenAI can charge hundreds (if not thousands) of percent more. So is that extra 6 percentage points in performance worth the colossal increase in cost?

It all boils down to your use case. If you’re a hedge fund manager who needs the absolute best of the best and every fraction of a percent could mean millions in revenue, you might still throw your money at the top-of-the-line model. But if you’re a mid-sized firm or an independent researcher, Perplexity’s offering is more than enough—especially at $20 a month.

Practical Implications: From Healthcare to Finance

Let’s look at some real-world scenarios. Healthcare professionals can use Deep Research to scour medical journals, clinical trial results, and official guidelines faster than you can say “NHS queue”. This means better patient outcomes, quicker insights, and less reliance on massive IT budgets.

Financial analysts can crunch market data, follow the latest economic news, and whip up in-depth reports that previously needed entire teams of well-paid data scientists. Technical documentation tasks become a breeze when Deep Research can parse through troves of manuals, development forums, and official documents in minutes.

Plus, Perplexity’s user-friendly features—like exporting findings as PDFs or sharing them directly through its platform—make collaboration straightforward. If you’ve ever had to wrestle with clunky enterprise software, you’ll appreciate the simplicity that Perplexity offers.

The Democratisation Ripple Effect

We’ve talked about how smaller entities stand to benefit from cheaper AI tools. But let’s not forget the social dimension. When you lower the barrier to entry, you empower not just businesses, but also students, civil society organisations, journalists, and independent researchers. Knowledge stops being locked behind corporate walls. That’s a big deal in Asia—where the digital transformation wave is sweeping nations at very different speeds and scales.

Imagine an NGO in a rural part of Southeast Asia that can now access top-notch AI research capabilities for $20 a month. That’s a giant leap forward in bridging the digital gap, enabling them to better serve local communities, gather data, and deliver more effective programmes. It’s not just a business story; it’s a social justice story too.

What’s Next in 2025 and Beyond?

Given that AI spending is expected to rise by 5.7% in 2025, the question on everyone’s lips is how this new wave of budget-friendly AI offerings will redistribute the market. Will companies continue throwing millions at established AI giants, or will they pivot to nimble, cost-effective alternatives like Perplexity?

In many ways, this sets the stage for an AI arms race of affordability and performance, where large players need to prove they’re worth the extra cash—or risk losing market share. From what we’re seeing, the AI community (and the public) are hungry for an open-source, reasonably priced alternative. Perplexity’s decision to offer a free daily query allowance and then a generous 500 queries a day for a mere $20 might be the blueprint for the future of AI subscription models.

The Jury’s Verdict and a New Era

So, does this mark the end of expensive AI subscriptions? We’ll have to wait and see. But one thing is clear: Perplexity’s Deep Research has seriously called into question the notion that you need to pay through the nose for quality AI. If performance is almost on par with more expensive services, or in some benchmarks better, why wouldn’t you jump on board?

Perhaps the biggest indicator of success will be user adoption. And it’s already looking promising—thousands of folks have begun testing Deep Research, singing its praises, and pondering whether they really need those thousand-dollar monthly fees. In the dynamic, ever-shifting AI world, the best technology won’t be the one with the biggest marketing budget but the one that’s truly accessible to the people who need it most.

There you have it, folks: a whirlwind tour of how a single innovation from Perplexity is rattling the foundations of AI’s business model. Whether you’re a budding researcher, a startup founder, or a corporate decision-maker, the paradigm is changing right before your eyes. Will you be part of the revolution—or left clinging to yesterday’s overpriced subscriptions? The choice, as always, is yours! And don’t forget to subscribe to keep up to date with all the latest AI happenings in Asia.

What Do YOU Think?

As AI costs plummet and quality soars, will businesses continue to pay premium prices out of habit—or dare to embrace the affordable future? Let us know in the comments below!

You may also like:

• Perplexity Deep Research Tool Debuts, Challenging OpenAI and Google
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• Or try Perplexity AI by tapping here.

TL;DR:

• ByteDance is planning to invest over $12 billion in AI infrastructure in 2025, with $5.5 billion allocated for AI chips in China and $6.8 billion dedicated to enhancing model training capabilities internationally.
• This move is aimed at strengthening ByteDance’s AI prowess to stay competitive against Chinese tech giants like Baidu, Alibaba, and Tencent.
• The investment includes a significant focus on acquiring Nvidia chips to bolster global AI initiatives.

If you’ve been keeping an eye on the tech world, ByteDance—the mastermind behind TikTok—is making headlines again. This time, they’re gearing up for a colossal $12 billion investment in AI infrastructure in 2025, according to the Financial Times. Let’s break down what this means and why it’s a big deal.

The Investment Breakdown

ByteDance’s ambitious plan involves:

1. $5.5 billion on AI chips in China: This substantial investment is set to double their spending from the previous year, highlighting a strong commitment to enhancing domestic AI capabilities.
2. $6.8 billion to boost global model training capabilities: A significant portion of this budget is earmarked for acquiring advanced Nvidia chips, underscoring ByteDance’s strategy to leverage top-tier technology for AI model training.

Why This Matters

1. Elevating AI Capabilities: With this hefty investment, ByteDance aims to elevate its AI infrastructure, ensuring that platforms like TikTok continue to offer cutting-edge features and personalised user experiences.
2. Staying Ahead in the AI Race: In the fiercely competitive tech landscape, this move positions ByteDance to keep pace with, or even outpace, rivals such as Baidu, Alibaba, and Tencent, all of whom are making significant strides in AI development.
3. Strategic Partnerships: By investing heavily in Nvidia chips, ByteDance is aligning itself with a leader in AI hardware, which could lead to more advanced and efficient AI models powering its platforms.

The Bigger Picture

This investment isn’t just about staying competitive; it’s about setting the stage for the future. As AI continues to evolve, companies that invest in robust infrastructure and cutting-edge technology will be better positioned to lead the market. ByteDance’s substantial commitment to AI underscores its vision to be at the forefront of this technological revolution.

Final Thoughts

ByteDance’s planned $12 billion investment in AI infrastructure is a bold move that signals its intent to lead in the AI-driven future. By focusing on both domestic and international advancements and partnering with industry leaders like Nvidia, ByteDance is not just keeping up with the competition—it’s setting the pace.

What are your thoughts on ByteDance’s massive AI investment? Let’s discuss in the comments below.

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TL;DR:

• Sir Elton John and Sir Paul McCartney are calling out AI for ripping off artists’ work—without paying a dime.
• They’re backing changes to the Data (Use and Access) Bill to protect copyrights in the age of generative AI.
• This is a global wake-up call: AI is amazing, but can creators afford to lose control of their own art?

What’s the Fuss About?

If you’ve been paying attention to the creative world lately, you’ve probably heard a lot about AI “stealing” from artists. Sounds dramatic, right? Well, it’s not just hype. Big names like Sir Elton John and Sir Paul McCartney are making some noise about how AI is being trained on artists’ works—without permission or payment.

Here’s the deal. AI systems, like the ones used to create fake Drake songs or uncanny art, need heaps of data to learn. That data? Often, it’s pulled from publicly available sources, which means your favourite song, artwork, or book might have been used to teach an AI how to mimic its style. And guess what? Nobody’s cutting cheques for the original creators.

The Legal Battleground: The Data (Use and Access) Bill

This is where the Data (Use and Access) Bill comes in. Right now, it’s under review in the UK, and some suggested amendments could be a game-changer. If approved, they’d make sure creators have a say (and get paid) when their work is used to train AI. Think of it as copyright protections 2.0—designed for the AI era.

Sir Elton and Sir Paul argue this is essential. Without such protections, creators might lose control of their own work, leaving the door open for corporations to profit off their creativity without a second thought. And let’s face it: that’s not a future anyone wants.

McCartney’s concerns are shared by a coalition of publishers, artists’ groups, and media organisations known as the Creative Rights in AI Coalition, which opposes weakening copyright protections.

Why Creators Are Worried

The backlash isn’t just about royalties (although, let’s be honest, that’s a big part of it). It’s also about authenticity. Imagine an AI-generated song using Sir Paul’s voice—but without his input or consent. Is it still “his” music? And if the lines between real and fake keep blurring, what happens to trust in the creative industry?

The tension is real:

• Creators say AI is exploiting their work without permission.
• AI advocates argue it’s all “fair use” and promotes innovation.
• Fans? They’re caught in the middle, wondering if the next viral song is even legit.

What’s Next for AI and Copyright?

The future of copyright and AI is still being written (pun intended). If the amendments to the Data (Use and Access) Bill pass, it could set a global precedent for how we protect creativity in the AI age. But legislation is only part of the solution.

Here’s what needs to happen:

1. Transparency: Companies need to be upfront about where their training data comes from.
2. Fair Compensation: If you’re using someone’s work, pay them for it. Simple.
3. Collaboration: Artists, lawmakers, and tech firms must find a balance that works for everyone.

Platforms like OpenAI are starting to take small steps, allowing rights holders to opt out of having their work used for training (source: OpenAI Blog, https://openai.com/blog). But let’s not kid ourselves—there’s a long way to go.

• And you can watch the interview with Paul McCartney here.
• You can read more about the proposed legislation and its potential impact on APNews.

The Big Question

AI is undeniably powerful, but it doesn’t replace human creativity. It’s like giving a robot a paintbrush—it can make something impressive, but does it have soul?

What do you think? Should AI have free reign to use whatever it wants, or is it time for tighter rules to protect creators?

Join the conversation, subscribe to our newsletter, and become part of our community of AI enthusiasts. Let’s shape the future of AI—together.

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