#AI is enabling smarter

[nostalgebraist]

Anthropic's stated "AI timelines" seem wildly aggressive to me.

As far as I can tell, they are now saying that by 2028 – and possibly even by 2027, or late 2026 – something they call "powerful AI" will exist.

And by "powerful AI," they mean... this (source, emphasis mine):

In terms of pure intelligence, it is smarter than a Nobel Prize winner across most relevant fields – biology, programming, math, engineering, writing, etc. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult codebases from scratch, etc. In addition to just being a “smart thing you talk to”, it has all the “interfaces” available to a human working virtually, including text, audio, video, mouse and keyboard control, and internet access. It can engage in any actions, communications, or remote operations enabled by this interface, including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on. It does all of these tasks with, again, a skill exceeding that of the most capable humans in the world. It does not just passively answer questions; instead, it can be given tasks that take hours, days, or weeks to complete, and then goes off and does those tasks autonomously, in the way a smart employee would, asking for clarification as necessary. It does not have a physical embodiment (other than living on a computer screen), but it can control existing physical tools, robots, or laboratory equipment through a computer; in theory it could even design robots or equipment for itself to use. The resources used to train the model can be repurposed to run millions of instances of it (this matches projected cluster sizes by ~2027), and the model can absorb information and generate actions at roughly 10x-100x human speed. It may however be limited by the response time of the physical world or of software it interacts with. Each of these million copies can act independently on unrelated tasks, or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations fine-tuned to be especially good at particular tasks.

In the post I'm quoting, Amodei is coy about the timeline for this stuff, saying only that

I think it could come as early as 2026, though there are also ways it could take much longer. But for the purposes of this essay, I’d like to put these issues aside [...]

However, other official communications from Anthropic have been more specific. Most notable is their recent OSTP submission, which states (emphasis in original):

Based on current research trajectories, we anticipate that powerful AI systems could emerge as soon as late 2026 or 2027 [...] Powerful AI technology will be built during this Administration. [i.e. the current Trump administration -nost]

See also here, where Jack Clark says (my emphasis):

People underrate how significant and fast-moving AI progress is. We have this notion that in late 2026, or early 2027, powerful AI systems will be built that will have intellectual capabilities that match or exceed Nobel Prize winners. They’ll have the ability to navigate all of the interfaces… [Clark goes on, mentioning some of the other tenets of "powerful AI" as in other Anthropic communications -nost]

----

To be clear, extremely short timelines like these are not unique to Anthropic.

Miles Brundage (ex-OpenAI) says something similar, albeit less specific, in this post. And Daniel Kokotajlo (also ex-OpenAI) has held views like this for a long time now.

Even Sam Altman himself has said similar things (though in much, much vaguer terms, both on the content of the deliverable and the timeline).

Still, Anthropic's statements are unique in being

official positions of the company

extremely specific and ambitious about the details

extremely aggressive about the timing, even by the standards of "short timelines" AI prognosticators in the same social cluster

Re: ambition, note that the definition of "powerful AI" seems almost the opposite of what you'd come up with if you were trying to make a confident forecast of something.

Often people will talk about "AI capable of transforming the world economy" or something more like that, leaving room for the AI in question to do that in one of several ways, or to do so while still failing at some important things.

But instead, Anthropic's definition is a big conjunctive list of "it'll be able to do this and that and this other thing and...", and each individual capability is defined in the most aggressive possible way, too! Not just "good enough at science to be extremely useful for scientists," but "smarter than a Nobel Prize winner," across "most relevant fields" (whatever that means). And not just good at science but also able to "write extremely good novels" (note that we have a long way to go on that front, and I get the feeling that people at AI labs don't appreciate the extent of the gap [cf]). Not only can it use a computer interface, it can use every computer interface; not only can it use them competently, but it can do so better than the best humans in the world. And all of that is in the first two paragraphs – there's four more paragraphs I haven't even touched in this little summary!

Re: timing, they have even shorter timelines than Kokotajlo these days, which is remarkable since he's historically been considered "the guy with the really short timelines." (See here where Kokotajlo states a median prediction of 2028 for "AGI," by which he means something less impressive than "powerful AI"; he expects something close to the "powerful AI" vision ["ASI"] ~1 year or so after "AGI" arrives.)

----

I, uh, really do not think this is going to happen in "late 2026 or 2027."

Or even by the end of this presidential administration, for that matter.

I can imagine it happening within my lifetime – which is wild and scary and marvelous. But in 1.5 years?!

The confusing thing is, I am very familiar with the kinds of arguments that "short timelines" people make, and I still find the Anthropic's timelines hard to fathom.

Above, I mentioned that Anthropic has shorter timelines than Daniel Kokotajlo, who "merely" expects the same sort of thing in 2029 or so. This probably seems like hairsplitting – from the perspective of your average person not in these circles, both of these predictions look basically identical, "absurdly good godlike sci-fi AI coming absurdly soon." What difference does an extra year or two make, right?

But it's salient to me, because I've been reading Kokotajlo for years now, and I feel like I basically get understand his case. And people, including me, tend to push back on him in the "no, that's too soon" direction. I've read many many blog posts and discussions over the years about this sort of thing, I feel like I should have a handle on what the short-timelines case is.

But even if you accept all the arguments evinced over the years by Daniel "Short Timelines" Kokotajlo, even if you grant all the premises he assumes and some people don't – that still doesn't get you all the way to the Anthropic timeline!

To give a very brief, very inadequate summary, the standard "short timelines argument" right now is like:

Over the next few years we will see a "growth spurt" in the amount of computing power ("compute") used for the largest LLM training runs. This factor of production has been largely stagnant since GPT-4 in 2023, for various reasons, but new clusters are getting built and the metaphorical car will get moving again soon. (See here)

By convention, each "GPT number" uses ~100x as much training compute as the last one. GPT-3 used ~100x as much as GPT-2, and GPT-4 used ~100x as much as GPT-3 (i.e. ~10,000x as much as GPT-2).

We are just now starting to see "~10x GPT-4 compute" models (like Grok 3 and GPT-4.5). In the next few years we will get to "~100x GPT-4 compute" models, and by 2030 will will reach ~10,000x GPT-4 compute.

If you think intuitively about "how much GPT-4 improved upon GPT-3 (100x less) or GPT-2 (10,000x less)," you can maybe convince yourself that these near-future models will be super-smart in ways that are difficult to precisely state/imagine from our vantage point. (GPT-4 was way smarter than GPT-2; it's hard to know what "projecting that forward" would mean, concretely, but it sure does sound like something pretty special)

Meanwhile, all kinds of (arguably) complementary research is going on, like allowing models to "think" for longer amounts of time, giving them GUI interfaces, etc.

All that being said, there's still a big intuitive gap between "ChatGPT, but it's much smarter under the hood" and anything like "powerful AI." But...

...the LLMs are getting good enough that they can write pretty good code, and they're getting better over time. And depending on how you interpret the evidence, you may be able to convince yourself that they're also swiftly getting better at other tasks involved in AI development, like "research engineering." So maybe you don't need to get all the way yourself, you just need to build an AI that's a good enough AI developer that it improves your AIs faster than you can, and then those AIs are even better developers, etc. etc. (People in this social cluster are really keen on the importance of exponential growth, which is generally a good trait to have but IMO it shades into "we need to kick off exponential growth and it'll somehow do the rest because it's all-powerful" in this case.)

And like, I have various disagreements with this picture.

For one thing, the "10x" models we're getting now don't seem especially impressive – there has been a lot of debate over this of course, but reportedly these models were disappointing to their own developers, who expected scaling to work wonders (using the kind of intuitive reasoning mentioned above) and got less than they hoped for.

And (in light of that) I think it's double-counting to talk about the wonders of scaling and then talk about reasoning, computer GUI use, etc. as complementary accelerating factors – those things are just table stakes at this point, the models are already maxing out the tasks you had defined previously, you've gotta give them something new to do or else they'll just sit there wasting GPUs when a smaller model would have sufficed.

And I think we're already at a point where nuances of UX and "character writing" and so forth are more of a limiting factor than intelligence. It's not a lack of "intelligence" that gives us superficially dazzling but vapid "eyeball kick" prose, or voice assistants that are deeply uncomfortable to actually talk to, or (I claim) "AI agents" that get stuck in loops and confuse themselves, or any of that.

We are still stuck in the "Helpful, Harmless, Honest Assistant" chatbot paradigm – no one has seriously broke with it since that Anthropic introduced it in a paper in 2021 – and now that paradigm is showing its limits. ("Reasoning" was strapped onto this paradigm in a simple and fairly awkward way, the new "reasoning" models are still chatbots like this, no one is actually doing anything else.) And instead of "okay, let's invent something better," the plan seems to be "let's just scale up these assistant chatbots and try to get them to self-improve, and they'll figure it out." I won't try to explain why in this post (IYI I kind of tried to here) but I really doubt these helpful/harmless guys can bootstrap their way into winning all the Nobel Prizes.

----

All that stuff I just said – that's where I differ from the usual "short timelines" people, from Kokotajlo and co.

But OK, let's say that for the sake of argument, I'm wrong and they're right. It still seems like a pretty tough squeeze to get to "powerful AI" on time, doesn't it?

In the OSTP submission, Anthropic presents their latest release as evidence of their authority to speak on the topic:

In February 2025, we released Claude 3.7 Sonnet, which is by many performance benchmarks the most powerful and capable commercially-available AI system in the world.

I've used Claude 3.7 Sonnet quite a bit. It is indeed really good, by the standards of these sorts of things!

But it is, of course, very very far from "powerful AI." So like, what is the fine-grained timeline even supposed to look like? When do the many, many milestones get crossed? If they're going to have "powerful AI" in early 2027, where exactly are they in mid-2026? At end-of-year 2025?

If I assume that absolutely everything goes splendidly well with no unexpected obstacles – and remember, we are talking about automating all human intellectual labor and all tasks done by humans on computers, but sure, whatever – then maybe we get the really impressive next-gen models later this year or early next year... and maybe they're suddenly good at all the stuff that has been tough for LLMs thus far (the "10x" models already released show little sign of this but sure, whatever)... and then we finally get into the self-improvement loop in earnest, and then... what?

They figure out to squeeze even more performance out of the GPUs? They think of really smart experiments to run on the cluster? Where are they going to get all the missing information about how to do every single job on earth, the tacit knowledge, the stuff that's not in any web scrape anywhere but locked up in human minds and inaccessible private data stores? Is an experiment designed by a helpful-chatbot AI going to finally crack the problem of giving chatbots the taste to "write extremely good novels," when that taste is precisely what "helpful-chatbot AIs" lack?

I guess the boring answer is that this is all just hype – tech CEO acts like tech CEO, news at 11. (But I don't feel like that can be the full story here, somehow.)

And the scary answer is that there's some secret Anthropic private info that makes this all more plausible. (But I doubt that too – cf. Brundage's claim that there are no more secrets like that now, the short-timelines cards are all on the table.)

It just does not make sense to me. And (as you can probably tell) I find it very frustrating that these guys are out there talking about how human thought will basically be obsolete in a few years, and pontificating about how to find new sources of meaning in life and stuff, without actually laying out an argument that their vision – which would be the common concern of all of us, if it were indeed on the horizon – is actually likely to occur on the timescale they propose.

It would be less frustrating if I were being asked to simply take it on faith, or explicitly on the basis of corporate secret knowledge. But no, the claim is not that, it's something more like "now, now, I know this must sound far-fetched to the layman, but if you really understand 'scaling laws' and 'exponential growth,' and you appreciate the way that pretraining will be scaled up soon, then it's simply obvious that –"

No! Fuck that! I've read the papers you're talking about, I know all the arguments you're handwaving-in-the-direction-of! It still doesn't add up!

[srbachchan]

DAY 6274

Jalsa, Mumbai Aopr 20, 2025 Sun 11:17 pm

🪔 ,

April 21 .. birthday greetings and happiness to Ef Mousumi Biswas .. and Ef Arijit Bhattacharya from Kolkata .. 🙏🏽❤️🚩.. the wishes from the Ef family continue with warmth .. and love 🌺

The AI debate became the topic of discussion on the dining table ad there were many potent points raised - bith positive and a little indifferent ..

The young acknowledged it with reason and able argument .. some of the mid elders disagreed mildly .. and the end was kind of neutral ..

Blessed be they of the next GEN .. their minds are sorted out well in advance .. and why not .. we shall not be around till time in advance , but they and their progeny shall .. as has been the norm through generations ...

The IPL is now the greatest attraction throughout the day .. particularly on the Sunday, for the two on the day .. and there is never a debate on that ..

🤣

.. and I am most appreciative to read the comments from the Ef on the topic of the day - AI .. appreciative because some of the reactions and texts are valid and interesting to know .. the aspect expressed in all has a legitimate argument and that is most healthy ..

I am happy that we could all react to the Blog contents in the manner they have done .. my gratitude .. such a joy to get different views , valid and meaningful ..

And it is not the end of the day or the debate .. some impressions of the Gen X and some from the just passed Gen .. and some that were never ever the Gen are interesting as well :

The Printing Press (15th Century)

Fear: Scribes, monks, and elites thought it would destroy the value of knowledge, lead to mass misinformation, and eliminate jobs. Reality: It democratized knowledge, spurred the Renaissance and Reformation, and created entirely new industries—publishing, journalism, and education.

⸻

Industrial Revolution (18th–19th Century)

Fear: Machines would replace all human labor. The Luddites famously destroyed machinery in protest. Reality: Some manual labor jobs were displaced, but the economy exploded with new roles in manufacturing, logistics, engineering, and management. Overall employment and productivity soared.

⸻

Automobiles (Early 20th Century)

Fear: People feared job losses for carriage makers, stable hands, and horseshoe smiths. Cities worried about traffic, accidents, and social decay. Reality: The car industry became one of the largest employers in the world. It reshaped economies, enabled suburbia, and created new sectors like travel, road infrastructure, and auto repair.

⸻

Personal Computers (1980s)

Fear: Office workers would be replaced by machines; people worried about becoming obsolete. Reality: Computers made work faster and created entire industries: IT, software development, cybersecurity, and tech support. It transformed how we live and work.

⸻

The Internet (1990s)

Fear: It would destroy jobs in retail, publishing, and communication. Some thought it would unravel social order. Reality: E-commerce, digital marketing, remote work, and the creator economy now thrive. It connected the world and opened new opportunities.

⸻

ATMs (1970s–80s)

Fear: Bank tellers would lose their jobs en masse. Reality: ATMs handled routine tasks, but banks actually hired more tellers for customer service roles as they opened more branches thanks to reduced transaction costs.

⸻

Robotics & Automation (Factory work, 20th century–today)

Fear: Mass unemployment in factories. Reality: While some jobs shifted or ended, others evolved—robot maintenance, programming, design. Productivity gains created new jobs elsewhere.

The fear is not for losing jobs. It is the compromise of intellectual property and use without compensation. This case is slightly different.

I think AI will only make humans smarter. If we use it to our advantage.

That’s been happening for the last 10 years anyway

Not something new

You can’t control that in this day and age

YouTube & User-Generated Content (mid-2000s onward)

Initial Fear: When YouTube exploded, many in the entertainment industry panicked. The fear was that copyrighted material—music, TV clips, movies—would be shared freely without compensation. Creators and rights holders worried their content would be pirated, devalued, and that they’d lose control over distribution.

What Actually Happened: YouTube evolved to protect IP and monetize it through systems like Content ID, which allows rights holders to:

Automatically detect when their content is used

Choose to block, track, or monetize that usage

Earn revenue from ads run on videos using their IP (even when others post it)

Instead of wiping out creators or studios, it became a massive revenue stream—especially for musicians, media companies, and creators. Entire business models emerged around fair use, remixes, and reactions—with compensation built in.

Key Shift: The system went from “piracy risk” to “profit partner,” by embracing tech that recognized and enforced IP rights at scale.

This lead to higher profits and more money for owners and content btw

You just have to restructure the compensation laws and rewrite contracts

It’s only going to benefit artists in the long run ‎

Yes

They can IP it

That is the hope

It’s the spread of your content and material without you putting a penny towards it

Cannot blindly sign off everything in contracts anymore. Has to be a lot more specific.

Yes that’s for sure

“Automation hasn’t erased jobs—it’s changed where human effort goes.”

Another good one is “hard work beats talent when talent stops working hard”

Which has absolutely nothing to with AI right now but 🤣

These ladies and Gentlemen of the Ef jury are various conversational opinions on AI .. I am merely pasting them for a view and an opinion ..

And among all the brouhaha about AI .. we simply forgot the Sunday well wishers .. and so ..

my love and the length be of immense .. pardon

Amitabh Bachchan

[zylentrix]

Transform Your Tomorrow with Zylentrix: Sustainable Innovation for Businesses, Careers, and Global Growth

🌐 Zylentrix: Redefining Success Through People-Centric Solutions

At Zylentrix, we’re on a mission to empower individuals, businesses, and communities through innovation, integrity, and sustainability. Our vision? To lead the world in integrated consultancy services, transforming challenges into stepping stones for growth. Whether you’re scaling a business, launching a career, or pursuing education, we’re here to equip you with the tools to thrive. Let’s unpack how our mission, values, and culture make us the partner you can trust.

🎯 Our Mission & Vision: The North Star of Zylentrix

Mission: “To empower individuals, businesses, and communities by delivering innovative and customised solutions across education, technology, recruitment, and business consulting. With a commitment to excellence, integrity, and sustainability, we strive to create opportunities, bridge gaps, drive transformation, and foster long-term success.”

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We’re not just consultants—we’re architects of progress, designing futures where everyone has the chance to excel.

💎 Core Values: The Pillars of Everything We Do

Our values are the blueprint for how we serve clients, collaborate with partners, and grow as a team:

Integrity: “Building Trust Through Transparency” Every decision is guided by ethics. No shortcuts, no compromises.

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At Zylentrix, our workplace is a launchpad for creativity and collaboration. Here’s what defines us:

Lifelong Learning: Monthly workshops, innovation challenges, and tuition reimbursements keep our team ahead of trends.

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Join the Zylentrix Movement

Ready to transform your business, career, or community? Let’s build a future where innovation and integrity go hand in hand.

📩 Connect Today 👉 Explore our services: Zylentrix 👉 Follow us on Social Media for tips on tech, careers, and sustainability. LinkedIn Facebook Instagram TikTok X Pinterest YouTube Quora Medium 👉 Email consult@zylentrix.net to schedule a free consultation.

[librarycards]

The narrative surrounding AI is that people will be “left behind” unless they adopt it ASAP. How is AI going to revolutionize education? How is it going to transform agriculture? How is it going to make logistics a million times smarter? Almost every sector is being faced with the proposition that they should jump on the AI train or risk getting left behind.

To my frustration, rather than having concerted, critical, and honest conversations around who benefits from this technology—and why and how—we’ve been sold the idea that it’s inevitable, and we better figure out how to make use of it, to deal with it as best we can.

I could see some approaches to AI being more punitive, like “I will do this and this if you use AI” [...] [but] I really wanted to approach my students as empowered agents of their own learning and to express to them, in the best way that I could at the time, what my reservations are. Not just with the tool in a technical sense and how it, as many people have confirmed, is much more like a stochastic parrot than it is something that learns or that is cognitive.

Beyond that, there is the larger “assemblage” of AI that enables these systems to run in the first place. Since I’m an environmental studies professor, it became clear that a lot of those pieces were an entire material world of energy, water, and other resources; of labor undervalued and exploited. And there’s the racialized and encoded assumptions that emanate through the texts upon which these chatbots are trained.

[almondenterprise]

Innovations in Electrical Switchgear: What’s New in 2025?

The electrical switchgear industry is undergoing a dynamic transformation in 2025, fueled by the rapid integration of smart technologies, sustainability goals, and the growing demand for reliable power distribution systems. As a key player in modern infrastructure — whether in industrial plants, commercial facilities, or utilities — switchgear systems are becoming more intelligent, efficient, and future-ready.

At Almond Enterprise, we stay ahead of the curve by adapting to the latest industry innovations. In this blog, we’ll explore the most exciting developments in electrical switchgear in 2025 and what they mean for businesses, contractors, and project engineers.

Rise of Smart Switchgear

Smart switchgear is no longer a futuristic concept — it’s a necessity in 2025. These systems come equipped with:

IoT-based sensors

Real-time data monitoring

Remote diagnostics and control

Predictive maintenance alerts

This technology allows for remote management, helping facility managers reduce downtime, minimize energy losses, and detect issues before they become critical. At Almond Enterprise, we supply and support the integration of smart switchgear systems that align with Industry 4.0 standards.

2. Focus on Eco-Friendly and SF6-Free Alternatives

Traditional switchgear often relies on SF₆ gas for insulation, which is a potent greenhouse gas. In 2025, there’s a significant shift toward sustainable switchgear, including:

Vacuum Interrupter technology

Air-insulated switchgear (AIS)

Eco-efficient gas alternatives like g³ (Green Gas for Grid)

These options help organizations meet green building codes and corporate sustainability goals without compromising on performance.

3. Wireless Monitoring & Cloud Integration

Cloud-based platforms are transforming how switchgear systems are managed. The latest innovation includes:

Wireless communication protocols like LoRaWAN and Zigbee

Cloud dashboards for real-time visualization

Integration with Building Management Systems (BMS)

This connectivity enhances control, ensures quicker fault detection, and enables comprehensive energy analytics for large installations

4. AI and Machine Learning for Predictive Maintenance

Artificial Intelligence is revolutionizing maintenance practices. Switchgear in 2025 uses AI algorithms to:

Predict component failure

Optimize load distribution

Suggest optimal switchgear settings

This reduces unplanned outages, increases safety, and extends equipment life — particularly critical for mission-critical facilities like hospitals and data centers.

5. Enhanced Safety Features and Arc Flash Protection

With increasing focus on workplace safety, modern switchgear includes:

Advanced arc flash mitigation systems

Thermal imaging sensors

Remote racking and switching capabilities

These improvements ensure safer maintenance and operation, protecting personnel from high-voltage hazards.

6. Modular & Scalable Designs

Gone are the days of bulky, rigid designs. In 2025, switchgear units are:

Compact and modular

Easier to install and expand

Customizable based on load requirements

Almond Enterprise supplies modular switchgear tailored to your site’s unique needs, making it ideal for fast-paced infrastructure developments and industrial expansions.

7. Global Standardization and Compliance

As global standards evolve, modern switchgear must meet new IEC and IEEE guidelines. Innovations include:

Improved fault current limiting technologies

Higher voltage and current ratings with compact dimensions

Compliance with ISO 14001 for environmental management

Our team ensures all equipment adheres to the latest international regulations, providing peace of mind for consultants and project managers.

Final Thoughts: The Future is Electric

The switchgear industry in 2025 is smarter, safer, and more sustainable than ever. For companies looking to upgrade or design new power distribution systems, these innovations offer unmatched value.

At Almond Enterprise, we don’t just supply electrical switchgear — we provide expert solutions tailored to tomorrow’s energy challenges. Contact us today to learn how our cutting-edge switchgear offerings can power your future projects.

[acuvate-updates]

How Agentic AI & RAG Revolutionize Autonomous Decision-Making

In the swiftly advancing realm of artificial intelligence, the integration of Agentic AI and Retrieval-Augmented Generation (RAG) is revolutionizing autonomous decision-making across various sectors. Agentic AI endows systems with the ability to operate independently, while RAG enhances these systems by incorporating real-time data retrieval, leading to more informed and adaptable decisions. This article delves into the synergistic relationship between Agentic AI and RAG, exploring their combined impact on autonomous decision-making.

Overview

Agentic AI refers to AI systems capable of autonomous operation, making decisions based on environmental inputs and predefined goals without continuous human oversight. These systems utilize advanced machine learning and natural language processing techniques to emulate human-like decision-making processes. Retrieval-Augmented Generation (RAG), on the other hand, merges generative AI models with information retrieval capabilities, enabling access to and incorporation of external data in real-time. This integration allows AI systems to leverage both internal knowledge and external data sources, resulting in more accurate and contextually relevant decisions.

Read more about Agentic AI in Manufacturing: Use Cases & Key Benefits

What is Agentic AI and RAG?

Agentic AI: This form of artificial intelligence empowers systems to achieve specific objectives with minimal supervision. It comprises AI agents—machine learning models that replicate human decision-making to address problems in real-time. Agentic AI exhibits autonomy, goal-oriented behavior, and adaptability, enabling independent and purposeful actions.

Retrieval-Augmented Generation (RAG): RAG is an AI methodology that integrates a generative AI model with an external knowledge base. It dynamically retrieves current information from sources like APIs or databases, allowing AI models to generate contextually accurate and pertinent responses without necessitating extensive fine-tuning.

Know more on Why Businesses Are Embracing RAG for Smarter AI

Capabilities

When combined, Agentic AI and RAG offer several key capabilities:

Autonomous Decision-Making: Agentic AI can independently analyze complex scenarios and select effective actions based on real-time data and predefined objectives.

Contextual Understanding: It interprets situations dynamically, adapting actions based on evolving goals and real-time inputs.

Integration with External Data: RAG enables Agentic AI to access external databases, ensuring decisions are based on the most current and relevant information available.

Enhanced Accuracy: By incorporating external data, RAG helps Agentic AI systems avoid relying solely on internal models, which may be outdated or incomplete.

How Agentic AI and RAG Work Together

The integration of Agentic AI and RAG creates a robust system capable of autonomous decision-making with real-time adaptability:

Dynamic Perception: Agentic AI utilizes RAG to retrieve up-to-date information from external sources, enhancing its perception capabilities. For instance, an Agentic AI tasked with financial analysis can use RAG to access real-time stock market data.

Enhanced Reasoning: RAG augments the reasoning process by providing external context that complements the AI's internal knowledge. This enables Agentic AI to make better-informed decisions, such as recommending personalized solutions in customer service scenarios.

Autonomous Execution: The combined system can autonomously execute tasks based on retrieved data. For example, an Agentic AI chatbot enhanced with RAG can not only answer questions but also initiate actions like placing orders or scheduling appointments.

Continuous Learning: Feedback from executed tasks helps refine both the agent's decision-making process and RAG's retrieval mechanisms, ensuring the system becomes more accurate and efficient over time.

Read more about Multi-Meta-RAG: Enhancing RAG for Complex Multi-Hop Queries

Example Use Case: Customer Service

Customer Support Automation Scenario: A user inquiries about their account balance via a chatbot.

How It Works: The Agentic AI interprets the query, determines that external data is required, and employs RAG to retrieve real-time account information from a database. The enriched prompt allows the chatbot to provide an accurate response while suggesting payment options. If prompted, it can autonomously complete the transaction.

Benefits: Faster query resolution, personalized responses, and reduced need for human intervention.

Example: Acuvate's implementation of Agentic AI demonstrates how autonomous decision-making and real-time data integration can enhance customer service experiences.

2. Sales Assistance

Scenario: A sales representative needs to create a custom quote for a client.

How It Works: Agentic RAG retrieves pricing data, templates, and CRM details. It autonomously drafts a quote, applies discounts as instructed, and adjusts fields like baseline costs using the latest price book.

Benefits: Automates multi-step processes, reduces errors, and accelerates deal closures.

3. Healthcare Diagnostics

Scenario: A doctor seeks assistance in diagnosing a rare medical condition.

How It Works: Agentic AI uses RAG to retrieve relevant medical literature, clinical trial data, and patient history. It synthesizes this information to suggest potential diagnoses and treatment options.

Benefits: Enhances diagnostic accuracy, saves time, and provides evidence-based recommendations.

Example: Xenonstack highlights healthcare as a major application area for agentic AI systems in diagnosis and treatment planning.

4. Market Research and Consumer Insights

Scenario: A business wants to identify emerging market trends.

How It Works: Agentic RAG analyzes consumer data from multiple sources, retrieves relevant insights, and generates predictive analytics reports. It also gathers customer feedback from surveys or social media.

Benefits: Improves strategic decision-making with real-time intelligence.

Example: Companies use Agentic RAG for trend analysis and predictive analytics to optimize marketing strategies.

5. Supply Chain Optimization

Scenario: A logistics manager needs to predict demand fluctuations during peak seasons.

How It Works: The system retrieves historical sales data, current market trends, and weather forecasts using RAG. Agentic AI then predicts demand patterns and suggests inventory adjustments in real-time.

Benefits: Prevents stockouts or overstocking, reduces costs, and improves efficiency.

Example: Acuvate’s supply chain solutions leverage predictive analytics powered by Agentic AI to enhance logistics operations

How Acuvate Can Help

Acuvate specializes in implementing Agentic AI and RAG technologies to transform business operations. By integrating these advanced AI solutions, Acuvate enables organizations to enhance autonomous decision-making, improve customer experiences, and optimize operational efficiency. Their expertise in deploying AI-driven systems ensures that businesses can effectively leverage real-time data and intelligent automation to stay competitive in a rapidly evolving market.

Future Scope

The future of Agentic AI and RAG involves the development of multi-agent systems where multiple AI agents collaborate to tackle complex tasks. Continuous improvement and governance will be crucial, with ongoing updates and audits necessary to maintain safety and accountability. As technology advances, these systems are expected to become more pervasive across industries, transforming business processes and customer interactions.

In conclusion, the convergence of Agentic AI and RAG represents a significant advancement in autonomous decision-making. By combining autonomous agents with real-time data retrieval, organizations can achieve greater efficiency, accuracy, and adaptability in their operations. As these technologies continue to evolve, their impact across various sectors is poised to expand, ushering in a new era of intelligent automation.

[carlhofelina]

Artificial Intelligence is more than just a buzzword—it's a powerful force shaping the way we work, live, and connect. As businesses and professionals navigate the rapidly changing digital landscape, AI integration has become not only an advantage but a necessity. From automating repetitive tasks to streamlining communication, AI is transforming the workplace—and now is the time to plug in.

What Is AI Integration?

AI integration refers to the process of embedding intelligent technology into your current systems and workflows. Instead of replacing human effort, it enhances capabilities by analysing data, learning patterns, and optimising operations in real-time. For professionals and organisations alike, this means better decisions, faster execution, and improved customer experiences.

Why Embrace AI Today?

Here’s how AI integration is making a difference across industries:

Improved Efficiency

With AI handling time-consuming tasks like email filtering, data analysis, and scheduling, teams can focus on what truly matters—innovation and human connection.

Smarter Decisions

 AI can process huge amounts of information quickly, offering insights that help businesses make better, data-backed choices.

Digital Strength

Today’s digital-first world demands a solid online presence. AI tools play a major role in Digital Presence Management, from optimising search visibility to curating consistent social media content.

Personal Branding 

Professionals and entrepreneurs are increasingly using AI-powered personal branding tools to craft compelling bios, automate content creation, and engage with audiences more effectively.

B2B Strategy

In a competitive market, B2B branding strategy supported by AI helps teams personalise outreach, understand client behaviour, and build stronger relationships.

Getting Started With AI Integration

Adopting AI doesn’t require a tech overhaul. Start with tools you may already be using:

Leverage Smart Features: Google Workspace, Microsoft 365, and Canva now include AI suggestions, writing assistants, and design tools.

Automate with Purpose: Platforms like Zapier or Make.com allow easy automation between your favourite apps and services.

Explore Industry Tools: If you’re in marketing, explore ChatGPT or Jasper for content. If you’re in customer service, check out AI-enabled platforms like Intercom or Drift.

Best Practices for a Smooth Transition

Educate Your Team: Offer basic training so everyone feels confident using AI tools.

Start with a Small Project: Test out AI on a single workflow, such as automating social media or customer queries.

Maintain Human Oversight: Always review AI outputs for accuracy and relevance.

Key Takeaways

AI integration is no longer optional—it's essential. Whether you're looking to improve productivity, enhance brand visibility, or gain a competitive edge, integrating AI is a smart step forward.

Visit Best Virtual Specialist to discover how our expert virtual professionals can help you integrate AI tools, elevate your digital presence, and transform your workflow. 

[thestudyiasbymanikantsingh]

Ukraine’s Devastating Strike on Russian Nuclear Assets Using AI-Powered Drones

The ongoing Russia-Ukraine conflict has dramatically evolved with the integration of Artificial Intelligence (AI) in modern warfare. Recently, Ukraine has showcased a striking example of how AI-enabled technology is reshaping battlefields. Under the codename “Operation Spiderweb,” Ukraine launched a series of precise, coordinated strikes deep inside Russian territory, targeting at least five key Russian airbases stretching from Siberia to Moscow. These airbases are vital military hubs from which Russia operates its missiles and warplanes, including the formidable TU-95 strategic bombers. Notably, these bombers were reportedly destroyed by AI-enabled Ukrainian drones, marking a significant turning point in the war.

This development signals a new dimension of drone warfare that is both low-cost and asymmetric, yet highly effective. Unlike traditional warfare, which heavily relies on large, expensive military hardware and personnel, the use of AI-powered drones allows smaller forces to strike critical infrastructure and assets with precision and stealth. The drones operate with advanced autonomy, enabling them to navigate hostile environments, evade detection, and carry out targeted attacks without risking human pilots or soldiers.

The psychological impact of these strikes is equally profound. The knowledge that a country’s core military assets can be attacked remotely by small, AI-driven machines erodes traditional notions of power and security. It challenges the dominance of heavy armor, fighter jets, and large-scale troop deployments that have defined warfare for decades.

Technology, precision, and psychological tactics have become the new pillars of modern conflicts. Ukraine’s successful deployment of AI-enabled drones underscores how warfare is no longer just about manpower and firepower but about who controls the smarter, faster, and more adaptive technology. This has forced Western powers to rethink strategic support and push for diplomatic pressure, evident in their ongoing efforts to leverage Istanbul as a platform for peace talks between Russia and Ukraine.

The message from these AI-powered drone attacks is clear: strategic power is undergoing a fundamental transformation. Traditional military superiority no longer guarantees battlefield dominance. Instead, innovative, cost-effective, and technologically advanced methods can disrupt even the most powerful adversaries.

This evolving scenario is not isolated to Ukraine and Russia. In response to this new wave of warfare, Pakistan launched its own drone strikes under Operation Sindoor, signaling that AI-powered drones have become a critical factor in regional security dynamics as well.

For countries like India, this shift presents both a challenge and an opportunity. The question is no longer if AI will play a role in future conflicts, but how well a country can integrate AI technology into its defense systems to protect its sovereignty and maintain strategic autonomy.

How can India prepare for these emerging threats without developing its own AI capabilities? The answer lies in accelerating investment in AI research, developing indigenous drone and counter-drone technologies, and building robust cyber-defense mechanisms. Additionally, strengthening international collaborations and intelligence-sharing can help anticipate and mitigate AI-driven threats.

The future of warfare will be shaped by those who harness AI effectively—not just for offense but also for defense. India, and indeed the global community, must adapt swiftly to this new reality, balancing innovation with strategic foresight to safeguard national security in an increasingly digital and unpredictable battlefield.

[gadgets7878]

Shocking Trends in Technology and Gadgets

Technology is advancing at an unprecedented pace, transforming not only our methods of communication but also our lifestyles, work habits, and thought processes. The year 2025 is set to be a pivotal moment in the development of gadgets and innovations that influence everyday life. From artificial intelligence and smart wearables to groundbreaking advancements in energy and computing, each innovation is redefining our expectations. What was once considered science fiction is now a reality and frequently integrated into our daily routines. As we anticipate a more interconnected, efficient, and immersive world, the latest trends illustrate a profound integration of technology with human experience.

These transformations extend well beyond merely new smartphone models or sleeker laptops. We are discussing trends that impact health, sustainability, communication, education, and even our experiences with entertainment. This article delves into the most significant and surprising trends in technology and gadgets as they unfold in 2025. Each segment examines how these advancements will influence various industries and what implications they hold for consumers and businesses alike.

For more details visit this

Whether you are a technology enthusiast, a professional in the industry, or simply an interested observer, grasping these forthcoming innovations is crucial. They are poised not only to change how we engage with the world but also to provide insights into the future direction of society. Prepare to discover twenty revolutionary trends that you cannot afford to miss.

II. The Ascendancy of Artificial Intelligence in Daily Life

Artificial Intelligence (AI) has transitioned from a specialized concept limited to researchers and engineers. By 2025, AI is becoming an integral aspect of everyday life, seamlessly woven into our daily activities. Smart assistants have evolved far beyond basic voice commands. They now provide proactive suggestions based on our habits, preferences, and surroundings.

Smartphones continue to be central to our digital lives, and 2025 brings some jaw-dropping innovations. Foldable and rollable displays are now mainstream, offering larger screens without increasing device size. These form factors enhance multitasking, gaming, and content consumption.

AI-powered cameras automatically adjust settings to capture professional-grade photos, recognize documents, and even analyze skin conditions. Battery life has also seen significant improvement thanks to more efficient processors and smarter power management systems.

Biometric enhancements such as under-display fingerprint sensors and facial mapping improve security. Additionally, smartphones now function as hubs for controlling other smart devices, from thermostats to vehicles.

With the integration of satellite connectivity, even remote areas enjoy reliable communication. These upgrades reflect a move toward devices that are not just tools but essential companions in managing digital and real-world tasks.

XI. Rise of the Metaverse

The metaverse has matured from hype to reality. In 2025, it’s a dynamic space for work, play, and socialization. Powered by VR and blockchain, the metaverse offers immersive experiences where users interact with digital environments and avatars.

Social media platforms are integrating metaverse elements, allowing users to attend concerts, business meetings, or even classrooms in virtual spaces. Commerce is thriving through virtual storefronts, where users can shop using cryptocurrency or NFTs.

Hardware advancements like lightweight VR headsets and motion-tracking wearables enhance immersion. Meanwhile, developers focus on interoperability, enabling avatars and assets to move seamlessly across platforms.

Whether it's remote work or digital tourism, the metaverse is reshaping how we connect and collaborate online.

XII. Smart Transportation and Electric Vehicles

Transportation is undergoing a revolution driven by electrification and automation. In 2025, electric vehicles (EVs) are more affordable and widespread, thanks to advances in battery technology and government incentives. EVs offer longer ranges, faster charging, and smart integration with home energy systems.

Self-driving car technology is progressing as well. Autonomous features like lane assist, adaptive cruise control, and automated parking are common. Ride-sharing companies are also piloting robo-taxis in urban centers.

Beyond cars, smart transportation includes connected bicycles, e-scooters, and drones. These innovations contribute to cleaner cities and more efficient travel.

Public transit is also getting smarter with real-time tracking, predictive maintenance, and eco-friendly buses. Together, these trends create a more sustainable and intelligent transportation ecosystem.

[leojoseph1978]

Bias in AI: The Glitch That Hurts Real People

Yo, Tumblr crew! Let’s chat about something wild: AI bias. Let’s discuss about AI’s everywhere—picking Netflix binge, powering self-driving cars, even deciding who will gets a job interview? It’s super cool, but here’s the tea: AI can mess up by favouring some people over others, and that’s a big deal. Let’s break down what’s going on, why it sucks, and how we can make things better.

What’s AI Bias?

Let’s imagine that AI is supposed to be a neutral, super-smart robot brain, right? But sometimes it’s more like that friend who picks favorites without even realizing it. AI bias is enables the system to screw up by treating certain groups unfairly—like giving dudes an edge in job applications or struggling to recognize faces of people with darker skin. It’s not the AI being a mis operational model; it’s just doing what it was taught, and sometimes its teaching is flawed.

AI bias and its insights

Shady Data: AI learns from data humans feed it. If that data’s from a world where, say, most tech hires were guys, the AI might “learn” to pick guys over others.

Human Oof Moments: People build AI, and we’re not perfect. Our blind spots—are thinking about how different groups are affected—can end up in the code.

Bad Design Choices: AI’s built can accidentally lean toward certain outcomes, like prioritizing stuff that seems “normal” but actually excludes people.

Why’s This a Big Deal?

A few years back, a big company ditched an AI hiring tool because it was rejecting women’s résumés. Yikes.

Facial recognition tech has messed up by misidentifying Black and Brown folks way more than white folks, even leading to wrongful arrests.

Ever notice job ads for high-paying gigs popping up more for guys?

This isn’t just a tech glitch—it’s a fairness issue. If AI keeps amplifying the same old inequalities, it’s not just a bug; it’s a system that’s letting down entire communities.

Where’s the Bias Coming From?

Old-School Data: If the data AI’s trained on comes from a world with unfair patterns (like, uh, ours), it’ll keep those patterns going. For example, if loan records show certain groups got denied more, AI might keep denying them too.

Not Enough Voices: If the folks building AI all come from similar backgrounds, they might miss how their tech affects different people. More diversity in the room = fewer blind spots.

Vicious Cycles: AI can get stuck in a loop. If it picks certain people for jobs, and only those people get hired, the data it gets next time just doubles down on the same bias.

Okay, How Do We Fix This?

There are ways to make things fairer, and it’s totally doable if we put in the work.

Mix Up the Data: Feed AI data that actually represents everyone—different races, genders, backgrounds.

Be Open About It: Companies need to spill the beans on how their AI works. No more hiding behind “it’s complicated.”

Get Diverse Teams: Bring in people from all walks of life to build AI. They’ll spot issues others might miss and make tech that works for everyone.

Keep Testing: Check AI systems regularly to catch any unfair patterns. If something’s off, tweak it until it’s right.

Set Some Ground Rules: Make ethical standards a must for AI. Fairness and accountability should be non-negotiable.

What Can we Do?

Spread the Word: Talk about AI bias! Share posts, write your own, or just chat with friends about it. Awareness is power.

Call It Out: If you see a company using shady AI, ask questions. Hit them up on social media and demand transparency.

Support the Good Stuff: Back projects and people working on fair, inclusive tech. Think open-source AI or groups pushing for ethical standards.

Let’s Dream Up a Better AI

AI’s got so much potential—think better healthcare, smarter schools, or even tackling climate change. By using diverse data, building inclusive teams, and keeping companies honest.

#AI #TechForGood #BiasInTech #MakeItFair #InclusiveFuture

@sruniversity

[stuarttechnologybob]

How does AI contribute to the automation of software testing?

AI-Based Testing Services

In today’s modern rapid growing software development competitive market, ensuring and assuming quality while keeping up with fast release cycles is challenging and a vital part. That’s where AI-Based Testing comes into play and role. Artificial Intelligence - Ai is changing the software testing and checking process by making it a faster, smarter, and more accurate option to go for.

Smart Test Case Generation:

AI can automatically & on its own analyze past test results, user behavior, and application logic to generate relevant test cases with its implementation. This reduces the burden on QA teams, saves time, and assures that the key user and scenarios are always covered—something manual processes might overlook and forget.

Faster Bug Detection and Resolution:

AI-Based Testing leverages the machine learning algorithms to detect the defects more efficiently by identifying the code patterns and anomalies in the code behavior and structure. This proactive approach helps and assists the testers to catch the bugs as early as possible in the development cycle, improving product quality and reducing the cost of fixes.

Improved Test Maintenance:

Even a small or minor UI change can break or last the multiple test scripts in traditional automation with its adaptation. The AI models can adapt to these changes, self-heal broken scripts, and update them automatically. This makes test maintenance less time-consuming and more reliable.

Enhanced Test Coverage:

AI assures that broader test coverage and areas are covered by simulating the realtime-user interactions and analyzing vast present datasets into the scenario. It aids to identify the edge cases and potential issues that might not be obvious to human testers. As a result, AI-based testing significantly reduces the risk of bugs in production.

Predictive Analytics for Risk Management:

AI tools and its features can analyze the historical testing data to predict areas of the application or product crafted that are more likely to fail. This insight helps the teams to prioritize their testing efforts, optimize resources, and make better decisions throughout the development lifecycle.

Seamless Integration with Agile and DevOps:

AI-powered testing tools are built to support continuous testing environments. They integrate seamlessly with CI/CD pipelines, enabling faster feedback, quick deployment, and improved collaboration between development and QA teams.

Top technology providers like Suma Soft, IBM, Cyntexa, and Cignex lead the way in AI-Based Testing solutions. They offer and assist with customized services that help the businesses to automate down the Testing process, improve the software quality, and accelerate time to market with advanced AI-driven tools.

[jcmarchi]

Stackpack Secures $6.3M to Reinvent Vendor Management in an AI-Driven Business Landscape

New Post has been published on https://thedigitalinsider.com/stackpack-secures-6-3m-to-reinvent-vendor-management-in-an-ai-driven-business-landscape/

Stackpack Secures $6.3M to Reinvent Vendor Management in an AI-Driven Business Landscape

In a world where third-party tools, services, and contractors form the operational backbone of modern companies, Stackpack has raised $6.3 million to bring order to the growing complexity.

Led by Freestyle Capital, the funding round includes support from Elefund, Upside Partnership, Nomad Ventures, Layout Ventures, MSIV Fund, and strategic angels from Intuit, Workday, Affirm, Snapdocs, and xAI.

The funding supports Stackpack’s mission to redefine how businesses manage their expanding vendor networks—an increasingly vital task as organizations now juggle hundreds or even thousands of external partners and platforms.

Turning Chaos into Control

Founded in 2023 by Sara Wyman, formerly of Etsy and Affirm, Stackpack was built to solve a problem she knew too well: modern companies are powered by vendors, yet most still track them with outdated methods—spreadsheets, scattered documents, and guesswork. With SaaS stacks ballooning and AI tools proliferating, unmanaged vendors become silent liabilities.

“Companies call themselves ‘people-first,’ but in reality, they’re becoming ‘vendor-first,’” said Wyman. “There are often 6x more vendors than employees. Yet there’s no system of record to manage that shift—until now.”

Stackpack gives finance and IT teams a unified, AI-powered dashboard that provides real-time visibility into vendor contracts, spend, renewals, and compliance risks. The platform automatically extracts key contract terms like auto-renewal clauses, flags overlapping subscriptions, and even predicts upcoming renewals buried deep in PDFs.

AI That Works Like a Virtual Vendor Manager

Stackpack’s Behavioral AI Engine acts as an intelligent assistant, surfacing hidden cost-saving opportunities, compliance risks, and critical dates. It not only identifies inefficiencies—it takes action, issuing alerts, initiating workflows, and providing recommendations across the vendor lifecycle.

For instance:

Renewal alerts prevent surprise charges.

Spend tracking identifies underused or duplicate tools.

Contract intelligence extracts legal and pricing terms from uploads or integrations with tools like Google Drive.

Approval workflows streamline onboarding and procurement.

This brings the kind of automation once reserved for enterprise procurement platforms like Coupa or SAP to startups and mid-sized businesses—at a fraction of the cost.

A Timely Solution for a Growing Problem

Vendor management has become a boardroom issue. As more companies shift budgets from headcount to outsourced services, compliance and financial oversight have become harder to maintain. Stackpack’s early traction is proof of demand: just months after launch, it’s managing over 10,500 vendors and $510 million in spend across more than 50 customers, including Every Man Jack, Rho, Density, HouseRx, Fexa, and ZeroEyes.

“The CFO is the one left holding the bag when things go wrong,” said Brandon Lee, Accounting Manager at BizzyCar. “Stackpack means we don’t have to cross our fingers every quarter.”

Beyond Visibility: Enabling Smarter Vendor Decisions

Alongside its core platform, Stackpack is launching Requests & Approvals, a lightweight tool to simplify vendor onboarding and purchasing decisions—currently in beta. The feature is already attracting customers looking for faster, more agile alternatives to traditional procurement systems.

With a long-term vision to help companies not only manage but discover and evaluate vendors more strategically, Stackpack is laying the groundwork for a smarter, interconnected vendor ecosystem.

“Every vendor decision carries legal, financial, and security consequences,” said Dave Samuel, General Partner at Freestyle Capital. “Stackpack is building the intelligent infrastructure to manage these relationships proactively.”

The Future of Vendor Operations

As third-party ecosystems grow in size and complexity, Stackpack aims to transform vendor operations from a liability into a competitive advantage. Its AI-powered approach gives companies a modern operating system for vendor management—one that’s scalable, proactive, and deeply integrated into finance and operations.

“This isn’t just about cost control—it’s about running a smarter company,” said Wyman. “Managing your vendors should be as strategic as managing your talent. We’re giving companies the tools to make that possible.”

With fresh funding and a rapidly expanding customer base, Stackpack is poised to become the new standard for how modern businesses manage the partners powering their growth.

[godstaff]

I always liked Martian Manhunter

I love the Martian.

What I hate is every other hero is explaining themselves to Batso almost like apologizing when he thinks he can do whatever he likes all the time. Who is he? The father figure of the JL?

DC is always catering for Batso fans.

Let's see:

Batso can't even clean his cesspool of a city from criminals, like he solemnly promised his perents in their very graves.

Batso couldn't protect his associates, all of them teens, getting five of them killed in different occasions. Lucky for him, writers resurrected all of them so he can save face and have a "happy batfamily". Needless to say he brought all of them to the dangerous "family business", even when many of them were pre-teens. Because he "didn't want them to turn up like him". They all are exactly like him: traumatized and unstable.

He made contingency plans for everything. Usually against everything, like his plans to take down his superpowerful colleagues, his plans to stage a war between the criminals in his city, or creating a powerful AI to take over the bodies of the people and turn them against the superheroes, his colleagues and "friends", like Brother Eye and the OMACs. What he didn't plan is what to do if those clever plans get stolen or get out of control because he didn't take enough precautions. He deemed himself smarter than everybody and his schemes could never be stolen and never can go wrong.

He was conveniently away, playing politics, when his city was stricken and isolated by an earthquake, leaving his associates to defend the city by themselves, without enough resources or exterior help (specially not from him), and, when he returned after the crisis was averted, strongly chided them for not doing what he would've done. Such role model. They did well, by the way. No thanks, No "good job!"s. Nothing.

He recruited the help of a girlfriend to play an assassination plot, so he couldn't be accused, but when she was incarcerated, he left her to fend for helself. Such gratitude.

When he has his back broken by Bane, he passed his mantle to a brutal and murderous deluded mystic vigilante, instead of his associates whom he himself trained for the job.

He's constantly playing tricks to his colleagues and "friends" to demonstrate he's smarter than all of them.

He constantly saves the life of a lunatic criminal clown and put him in a jail he knows could never hold him, because "he doesn't kill". The clown always escapes, killing hundreds just to call his attention. But Batso considers his hands are clean of the blood of innocent people.

Batso is unimpeachable, and the other heroes are enablers, thanks to the fanboy writers.

As written, no reasonable person would trust his criteria about anything. And these are the mistakes I remember from the top of my head. There are more, much more.

Nobody ever says Batso is a stupid "Know it all" who thinks he can't make mistakes.

I love that J'onn confronts him when he, as he always do, loves to point out what the others do wrong.

I believe Batso thinks it is his unspoken duty to tell others "I told you so", but he would never allow them to do the same to him. Not even if they are right, not even if it helps.

Fortunately, Selina said: "Nope. No way. You are a decent booty call, but not a reliable life partner. I don't need somebody crazier than me."

[viscousspiritmyth]

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[mhdfadhil]

The Rise of Smart Homes in Abu Dhabi: Is It Worth the Investment?

 🌐 Visit: www.purehome-re.ae

As Abu Dhabi continues to evolve as a future-forward, tech-savvy city, one of the most significant shifts in the real estate market is the growing demand for smart homes. But what exactly are smart homes—and why are they becoming such an attractive option for both buyers and investors in 2025?

What Are Smart Homes?

Smart homes are residential properties equipped with advanced automation systems that control lighting, temperature, security, appliances, and more. These features are designed to offer convenience, energy efficiency, and enhanced security, creating a seamless and responsive living environment.

In Abu Dhabi, this movement is not just a trend—it’s part of a larger government vision to build AI-powered, sustainable communities that cater to modern living standards.

Key Benefits of Investing in Smart Homes in Abu Dhabi

1. Energy Efficiency & Cost Savings Smart homes use AI-enabled systems to manage energy consumption intelligently. Features like smart lighting, thermostats, and solar integrations help reduce utility costs, making them more appealing for long-term living and investment.

2. Advanced Security Integrated security systems—such as facial recognition, remote monitoring, and automated emergency alerts—provide peace of mind for residents and families. These features are particularly in demand among expats relocating to the UAE.

3. Sustainability & Water Management With smart irrigation systems and leak-detection technology, these homes support water conservation efforts, aligning with Abu Dhabi’s broader sustainability goals.

4. Health & Wellness Features Some smart residences now come equipped with indoor air quality monitors, automated air purifiers, and even health-tracking integrations—further enhancing the lifestyle benefits.

Why Now Is the Time to Invest

Abu Dhabi’s real estate trends for 2025 point to a surge in demand for smart, eco-conscious living spaces. Government support for smart city initiatives, the rise of communities like Al Reem Island, Yas Island, and Masdar City, and an increase in remote work flexibility have made smart homes a sound investment choice.

According to recent reports, buyers are actively searching for:

Smart villas in Yas Island

Energy-efficient homes in Masdar City

Luxury apartments with automation in Al Reem Island

These preferences show that smart homes aren’t just futuristic—they’re the present.

Final Thoughts

Smart homes in Abu Dhabi are reshaping the way people think about real estate. Whether you're an investor looking for high ROI or a resident seeking convenience, sustainability, and security, smart living offers a compelling proposition.

Ready to Invest in a Smarter Future?

At Pure Home Real Estate, we help you find innovative, tech-integrated properties tailored to your lifestyle or investment goals. 📩 Contact us today to explore the best smart home listings across Abu Dhabi. 📞 Call: +971 2 446 6775 🌐 Visit: www.purehome-re.aes