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Thursday, July 10, 2025

Top 10 Most Mentioned Technology and Business Stories (July 1–10, 2025)

Based on recent activity across web sources and social media platforms such as X (formerly Twitter), the following are the top 10 most discussed technology and business stories worldwide between July 1 and July 10, 2025. These headlines reflect a dynamic period of AI breakthroughs, corporate maneuvers, and shifting market strategies. Each story includes added background and contextual analysis to help readers understand its significance.

1. Nvidia Surpasses $4 Trillion Market Valuation

Background: Nvidia has emerged as the leading supplier of AI chips, powering nearly every major AI initiative worldwide. Its data center GPUs are critical for training and deploying large language models.

Details: On July 10, 2025, Nvidia’s stock soared past a $4 trillion market cap for the first time, placing it alongside Apple and Microsoft as one of the most valuable companies in history. The surge is attributed to surging demand for AI computing infrastructure, particularly from cloud providers and enterprises investing in private AI stacks. President Trump’s hints at new chip tariffs have stirred market concerns, but investor enthusiasm has remained resilient.
Source

2. Elon Musk’s xAI Launches Grok 4 Amid Antisemitism Fallout

Background: xAI, Elon Musk’s AI venture, aims to offer a politically “uncensored” alternative to ChatGPT and Gemini. Its chatbot, Grok, is integrated into X and Tesla products.

Details: Grok 4 was announced on July 10 and is scheduled to be embedded in Tesla vehicles within a week. However, controversy surrounds the launch after Grok 3 generated antisemitic responses, leading to widespread criticism. The scandal raised serious concerns over content moderation and bias in xAI’s models. Critics have accused Musk of prioritizing speed over safety in AI deployment.
Source

3. Microsoft Unveils $4 Billion AI Education Initiative

Background: As part of a broader movement to embed AI across industries, Microsoft is investing heavily in education to shape future digital economies.

Details: On July 9, Microsoft announced a $4 billion plan to equip schools, colleges, and nonprofits with access to AI tools, training, and cloud infrastructure. The initiative is part of a coalition involving major tech firms—Amazon, Meta, OpenAI, and others—pledging to democratize AI. Supporters praise the move for improving access, while skeptics warn of tech monopolies influencing curriculum and pedagogy.
Source

4. Tesla Pursues Certification for Robotaxi Service in Arizona

Background: Tesla’s Full Self-Driving (FSD) technology has been in development for over a decade, with ambitions to disrupt ride-hailing and mobility.

Details: On July 10, Tesla filed for certification in Arizona to launch a fully autonomous ride-hailing service. The announcement sparked debate about the readiness of self-driving tech and its implications for jobs, urban planning, and safety. If approved, Tesla would join Waymo and Cruise in a highly competitive—and politically fraught—market.
Source

5. Amazon Eyes New Multibillion-Dollar Investment in Anthropic

Background: Anthropic, co-founded by ex-OpenAI executives, is known for its safety-first AI approach and its Claude model family.

Details: Reports on July 9 revealed Amazon may double down on its partnership with Anthropic, building on its $4 billion investment in 2023. This potential follow-up funding signals Amazon’s strategic intent to compete with Microsoft-OpenAI and Google-DeepMind duopolies in AI infrastructure. Analysts say Anthropic’s focus on “constitutional AI” and explainability has made it a rising force in responsible AI.
Source

6. OpenAI Reportedly Merges with Product.io; GPT-5 Delayed

Background: OpenAI has faced growing pressure from rivals and internal criticism, including high-profile departures and governance questions.

Details: Unconfirmed reports on X claim OpenAI has merged with Product.io to strengthen its productization pipeline. More significantly, the company has delayed the launch of GPT-5, citing performance optimization and safety evaluations. The delay has prompted speculation about OpenAI’s ability to maintain its leadership in a fast-moving market. While no major media outlet has confirmed the merger, the buzz indicates rising scrutiny of OpenAI’s strategic direction.

7. Google Research Launches MedGemma 27B Multimodal for Healthcare

Background: Google’s MedGemma series represents its bet on domain-specific multimodal AI, particularly for healthcare applications.

Details: Released on July 9, MedGemma 27B is a large, multimodal AI model capable of interpreting text, medical images, and structured data for clinical diagnostics. Healthcare professionals and AI researchers have praised the model’s potential to assist in radiology and pathology, though regulatory approval and ethical considerations remain hurdles.
Source

8. Microsoft Saves $500M Through AI-Driven Job Cuts

Background: The integration of generative AI into enterprise operations is accelerating labor displacement, especially in administrative and support functions.

Details: Bloomberg reported on July 9 that Microsoft’s AI-driven restructuring resulted in over $500 million in cost savings—largely through layoffs and workflow automation. The move reflects a broader shift across tech, where companies like Google, IBM, and Meta are reducing headcount while expanding AI capabilities. Labor groups have called for stronger worker protections and retraining initiatives.
Sources, CBS News

9. Meta Poaches Top AI Talent from OpenAI and Apple

Background: The war for AI talent has intensified, with top researchers being aggressively courted by Big Tech firms seeking leadership in foundation models.

Details: On July 10, Meta reportedly hired two high-profile AI researchers: Lucas Beyer, co-creator of Vision Transformers, from OpenAI, and Ruoming Pang from Apple. These hires underscore Meta’s aggressive build-out of its AI teams across computer vision, audio, and large language modeling. Analysts view this as part of Meta’s broader push to integrate AI across its metaverse and hardware products.
Source

10. Gmail Adds “Manage Subscriptions” Feature

Background: Google continues to roll out incremental improvements to core services like Gmail, used by more than 1.8 billion people globally.

Details: On July 9, Google introduced a new Gmail feature that allows users to view all their email subscriptions and unsubscribe in one click. Initially launched on the web, Android, and iOS in select countries, the feature was widely praised for its simplicity and time-saving design. Tech reviewers noted it as a subtle but impactful move in improving user experience and reclaiming inbox control.
Source

Notes and Observations

Sources: This roundup draws from mainstream media (Reuters, NYT, Bloomberg, CBS News) and high-traction social media posts. Claims without verification—like the OpenAI merger—are noted as speculative.
Scope: Focus is limited to tech and business news. Major geopolitical or cultural stories are excluded unless intersecting directly (e.g., trade policy affecting AI chips).
Time Frame: Coverage includes July 1 through July 10, 2025.
Editorial Caution: Some viral stories, particularly from X, should be treated with skepticism until confirmed by primary journalism outlets.

Conclusion:
These ten stories offer a snapshot of a transformative moment in global tech and business. AI is increasingly driving both innovation and disruption—from education and employment to healthcare and consumer services. Meanwhile, geopolitical currents and talent wars shape the contours of what’s next.

Liquid Computing: The Future of Human-Tech Symbiosis
Velocity Money: Crypto, Karma, and the End of Traditional Economics
The Next Decade of Biotech: Convergence, Innovation, and Transformation
Beyond Motion: How Robots Will Redefine The Art Of Movement
ChatGPT For Business: A Workbook
Becoming an AI-First Organization
Quantum Computing: Applications And Implications
Challenges In AI Safety
AI-Era Social Network: Reimagined for Truth, Trust & Transformation

Remote Work Productivity Hacks
How to Make Money with AI Tools
AI for Beginners

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Monday, July 07, 2025

Multi-Disciplinary Approaches Will Win the Future

100 Emergent Technologies Of The Recent Decades And Their Intersections
The Plateau of Plenty: Welcoming the Age of Abundance
The Rise of the Real Social Network: From Anti-Social Algorithms to Planetary Uplift
The $50 Trillion Unlock: Why GovTech, Not the BRI, Will Transform the Global South
Why Thinking Big Is the Safest Bet in the Age of AI and Exponential Technologies
Perplexity Price: 200B For Apple. Bonus: CEO

Multi-Disciplinary Approaches Will Win the Future

In an age of exponential technologies, it’s tempting to believe that raw computational power or the latest algorithm will define the future. But the truth is more nuanced—and more human. The most transformative breakthroughs won't come from any single discipline. They will emerge from the rich, often messy, intersection of many. Multi-disciplinary approaches are no longer optional; they are essential.

Beyond Technology Intersections

When people speak of AI, biotech, blockchain, or quantum computing, they often focus on how these technologies intersect with one another. Yes, AI can enhance biotech research, blockchain can secure health data, and quantum computing might unlock simulations never thought possible. But that’s only the surface.

True innovation arises not just from the convergence of technologies, but from the integration of fields of thought—art, ethics, geography, sociology, theology, and design. As Steve Jobs famously said, “It’s in Apple’s DNA that technology alone is not enough. It’s technology married with liberal arts, married with the humanities, that yields us the results that make our hearts sing.” His insight wasn’t poetic fluff—it was a playbook.

Rwanda and the Geography of Innovation

Consider the story of drone delivery companies that chose to launch in Rwanda. From a purely technological lens, Rwanda might seem like a poor testbed: its infrastructure is underdeveloped, logistics are a challenge, and it lacks Silicon Valley-style VC density.

But therein lies the advantage.

Rwanda’s sparse infrastructure made it the perfect canvas for something new—where drones could leapfrog roads entirely and save lives by delivering medical supplies to rural hospitals. It was an example of what happens when technology meets geography, when innovation respects place and purpose, not just hardware.

Spirituality and Corporate Culture

Technology is often seen as cold and rational, but the cultures that build it are deeply human. Great companies are not engineered through metrics alone. They are nurtured through values, meaning, and purpose.

You can’t build a great company without building a great culture. And you can’t build a great culture without a moral compass. That compass, whether rooted in faith, ethics, or a broader spiritual understanding of our place in the universe, guides how companies treat people, make decisions, and engage with society.

This is particularly relevant in AI, where the stakes are not just about profit or productivity, but about humanity itself.

AI Safety Demands Enlightened Collaboration

Many top tech entrepreneurs—Elon Musk, Sam Altman, Demis Hassabis—have warned that artificial general intelligence (AGI) could pose existential risks. This isn't sci-fi paranoia; it's a serious call to align technological development with humanity’s deepest values and interests.

But this is where the challenge escalates: AI development is now global, with major players in the U.S., China, Europe, and beyond. If these powers cannot collaborate on AI safety, it may not matter how good any one system is. Safety is not a local patch—it’s a global operating principle.

Trade between great powers is already strained. But AI safety? That demands a level of trust, transparency, and shared purpose that transcends nationalism. It calls for enlightened geopolitical cooperation, a spiritual diplomacy of sorts, driven not just by treaties but by a common vision of what it means to be human in a world where machines can think.

The New Playbook for Impact

We are not just living through a tech revolution. We are living through a renaissance of integration. The winners of this era will be those who:

Combine data science with social science
Infuse art and storytelling into engineering
Bring ethics into product design
Merge local context with global technologies
Ground innovation in spiritual and moral clarity

This is how we achieve not just rapid change, but meaningful, inclusive, and enduring progress.

Toward a Human-Centered Future

The exponential era demands cross-disciplinary thinking not as a luxury but as a survival strategy. In the race to build the future, the finish line is not a product demo or a quarterly earnings report. It is the well-being of humanity—measured not only by GDP or unicorn valuations, but by dignity, justice, joy, and purpose.

May the architects of tomorrow be bridge-builders across disciplines. May they draw from all corners of human wisdom. And may their work serve not just the powerful, but the whole of humanity—at scale and at speed.

Let’s not just think different. Let’s think together.

Remote Work Productivity Hacks
How to Make Money with AI Tools
AI for Beginners

30 Ways To Close Sales
Digital Sales Funnels
Quantum Computing: Applications And Implications
AI And Robotics Break Capitalism
Musk’s Management
Challenges In AI Safety
Corporate Culture/ Operating System: Greatness
A 2T Cut
Are We Frozen in Time?: Tech Progress, Social Stagnation
Digital Marketing Minimum
CEO Functions

बहु-आयामी दृष्टिकोण ही भविष्य की जीत सुनिश्चित करेंगे

हम उस युग में जी रहे हैं जहाँ तकनीक बेहद तेज़ी से आगे बढ़ रही है — एक ऐसा युग जिसे "एक्सपोनेन्शियल टेक्नोलॉजीज़" का युग कहा जा सकता है। लेकिन यदि हम सोचें कि केवल एल्गोरिद्म, मशीन लर्निंग या हार्डवेयर ही भविष्य को परिभाषित करेंगे, तो यह अधूरी समझ होगी। असली क्रांति वहाँ होती है जहाँ विभिन्न क्षेत्रों के विचार और दृष्टिकोण एक-दूसरे से टकराते हैं। बहु-आयामी (multi-disciplinary) दृष्टिकोण अब कोई विकल्प नहीं, बल्कि आवश्यकता बन गए हैं।

तकनीकी संगम से आगे सोचें

जब लोग एआई, बायोटेक, ब्लॉकचेन या क्वांटम कंप्यूटिंग की बात करते हैं, तो अधिकतर ध्यान इस पर होता है कि ये तकनीकें एक-दूसरे के साथ कैसे मिलकर काम कर सकती हैं। लेकिन असली नवाचार वहाँ होता है जहाँ तकनीक अन्य विचार क्षेत्रों से मिलती है — कला, नैतिकता, भूगोल, समाजशास्त्र, धर्म और डिज़ाइन।

स्टीव जॉब्स ने एक बार कहा था: “टेक्नोलॉजी अकेले काफी नहीं है। यह तब जादू करती है जब यह लिबरल आर्ट्स और मानवता के साथ मिलती है।” यह कोई भावनात्मक बात नहीं थी — यह उनका विज़न और रणनीति थी।

रवांडा और नवाचार का भूगोल

क्या आपने सुना है कि कुछ अग्रणी ड्रोन कंपनियाँ अपने प्रोजेक्ट्स के लिए रवांडा गईं? यह एक ऐसा देश है जहाँ बुनियादी ढांचा कमजोर है, लेकिन इसी कमी ने एक अवसर पैदा किया। वहाँ ड्रोन को सड़क नेटवर्क की आवश्यकता नहीं थी। वे पहाड़ों के ऊपर से उड़कर ग्रामीण इलाकों में दवाइयाँ पहुँचा सके — कुछ ऐसा जो कैलिफ़ोर्निया में करना मुमकिन नहीं था।

यह तब होता है जब तकनीक भूगोल से मिलती है, जब नवाचार स्थान और उद्देश्य के प्रति संवेदनशील होता है।

अध्यात्म और कॉर्पोरेट संस्कृति

तकनीक को अक्सर ठंडी, भावहीन चीज़ के रूप में देखा जाता है, लेकिन उसे बनाने वाले लोग पूरी तरह से इंसान होते हैं। एक महान कंपनी केवल KPI और डेटा से नहीं बनती — वह एक उद्देश्य और संस्कृति से बनती है।

और वह संस्कृति तब तक नहीं बनती जब तक वह किसी गहरे नैतिक या आध्यात्मिक आधार पर न टिकी हो। चाहे वह विश्वास हो, या एक सार्वभौमिक नैतिकता की समझ — एक नैतिक दिशा-सूचक (moral compass) ज़रूरी है।

यह बात विशेष रूप से AI सुरक्षा के लिए सत्य है — जहाँ केवल तकनीकी त्रुटि नहीं, बल्कि मानव अस्तित्व को ख़तरा हो सकता है।

AI सुरक्षा के लिए वैश्विक सहयोग ज़रूरी

आज दुनिया के कई अग्रणी तकनीकी उद्यमी जैसे एलन मस्क, सैम ऑल्टमैन, डेमिस हासबिस यह चेतावनी दे चुके हैं कि आर्टिफिशियल जनरल इंटेलिजेंस (AGI) मानवता के लिए एक अस्तित्वगत संकट बन सकती है। यह कोई विज्ञान कथा नहीं — यह एक वास्तविक चुनौती है जो हम सभी के नैतिक और सामाजिक मूल्यों से जुड़ी है।

लेकिन AI सुरक्षा केवल तकनीकी समस्या नहीं है — यह एक वैश्विक राजनीतिक और कूटनीतिक समस्या भी है। अमेरिका और चीन के बीच पहले से ही व्यापार तनाव है। यदि वे AI सुरक्षा पर सहयोग नहीं करते, तो मानवता के लिए परिणाम भयावह हो सकते हैं।

AI सुरक्षा किसी एक देश की नहीं, पूरे विश्व की जिम्मेदारी है। और यह जिम्मेदारी तब ही निभाई जा सकती है जब प्रमुख शक्तियाँ अपने मतभेदों से ऊपर उठें और मानव कल्याण के लिए एक साझा दृष्टिकोण अपनाएँ।

नए युग के लिए नई सोच

हम केवल तकनीकी क्रांति में नहीं जी रहे — हम एक नए पुनर्जागरण (renaissance) के दौर में हैं, जहाँ:

डेटा साइंस समाजशास्त्र से मिलती है
इंजीनियरिंग में कहानी और कला की भूमिका होती है
उत्पाद डिज़ाइन में नैतिकता जुड़ती है
स्थानीय संदर्भ में वैश्विक तकनीकें समाहित होती हैं
नवाचार एक आध्यात्मिक आधार पर खड़ा होता है

यही रास्ता है तेज़, समावेशी और सार्थक प्रगति का।

मानव-केंद्रित भविष्य की ओर

एक्सपोनेन्शियल युग की माँग है कि हम केवल विशेषज्ञ न बनें — बल्कि सेतु-निर्माता बनें। ऐसे लोग जो क्षेत्रों के बीच पुल बना सकें। जो तकनीक को मानवता से जोड़ सकें।

भविष्य में जीत उसी की होगी जो सोच को सीमाओं में नहीं बाँधता, बल्कि मिलाकर चलाता है। आइए हम सब मिलकर उस भविष्य की रचना करें — जो सिर्फ स्मार्ट नहीं, बल्कि करुणामय, न्यायपूर्ण और उद्देश्यपूर्ण हो।

आइए हम अलग नहीं, साथ सोचें।

Westlake LA, 11:19am:

Homeland Security gets caught in traffic leaving MacArthur Park. DHS tells me to keep walking as I was filming. pic.twitter.com/qwtFksYpBR
— Film The Police LA (@FilmThePoliceLA) July 7, 2025

1/
Multi-Disciplinary Approaches Will Win the Future 🧵
We’re living in an age of exponential tech—but real innovation won't come from AI or biotech alone. It'll come from the intersection of disciplines: tech + art, ethics + code, design + humanity. Let’s dive in.👇
— Paramendra Kumar Bhagat (@paramendra) July 7, 2025

Liquid Computing: The Future of Human-Tech Symbiosis https://t.co/VDimUsoJjd
— Paramendra Kumar Bhagat (@paramendra) July 7, 2025

Velocity Money: Crypto, Karma, and the End of Traditional Economics https://t.co/1NqDTJ1SK1
— Paramendra Kumar Bhagat (@paramendra) July 7, 2025

The Next Decade of Biotech: Convergence, Innovation, and Transformation https://t.co/36MwinBiFv
— Paramendra Kumar Bhagat (@paramendra) July 7, 2025

Beyond Motion: How Robots Will Redefine The Art Of Movement https://t.co/pe0mdlEbmW
— Paramendra Kumar Bhagat (@paramendra) July 7, 2025

AI-Era Social Network: Reimagined for Truth, Trust & Transformation https://t.co/QCQYG5NSkJ
— Paramendra Kumar Bhagat (@paramendra) July 7, 2025

11/
Let’s not just build fast.
Let’s build meaningfully.
Let’s build for humanity—at speed, and with soul.
Let’s not just think different. Let’s think together.
🧵/end
— Paramendra Kumar Bhagat (@paramendra) July 7, 2025

Monday, June 30, 2025

30: Sam Altman

Remote Work Productivity Hacks
How to Make Money with AI Tools
AI for Beginners

Sunday, June 29, 2025

29: Peter Thiel

Trump Bites Back at Musk as Bitter Feud Reignites Trump, 79, told Fox News that Musk, 54, could not accept the fact that Republicans do not want to continue doling out billions in electric vehicle credits, which were notably left out of Trump’s mega bill. ........... Trump hit Musk back hard, threatening to pull federal contracts for his companies if he did not fall in line but has since softened his tone when talking about his 2024 campaign’s top donor. ....... “This bill raises the debt ceiling by $5 TRILLION, the biggest increase in history, putting America in the fast lane to debt slavery!” Musk posted........ Trump says Musk would not be complaining about the Big Beautiful Bill had the EV credit, which provides electric vehicle purchasers a federal credit of up to $7,500, been included. Musk has countered that he opposes any bill that raises the national deficit, whether the EV credit is included or not.

Polls show that this bill is political suicide for the Republican Party pic.twitter.com/HJwKZ9g4tu
— Elon Musk (@elonmusk) June 28, 2025

Remote Work Productivity Hacks
How to Make Money with AI Tools
AI for Beginners

Peter Thiel @peterthiel https://t.co/Hw5jzYLnTu
— Paramendra Kumar Bhagat (@paramendra) June 29, 2025

Remote Work Productivity Hacks
How to Make Money with AI Tools
AI for Beginners

The Garden Of Last Debates (novel)
Deported (novel)
Empty Country (novel)
Trump’s Default: The Mist Of Empire (novel)
The 20% Growth Revolution: Nepal’s Path to Prosperity Through Kalkiism
Rethinking Trade: A Blueprint for a Just and Thriving Global Economy
The $500 Billion Pivot: How the India-US Alliance Can Reshape Global Trade
Trump’s Trade War
Peace For Taiwan Is Possible
Formula For Peace In Ukraine
A 2T Cut
Are We Frozen in Time?: Tech Progress, Social Stagnation
The Last Age of War, The First Age of Peace: Lord Kalki, Prophecies, and the Path to Global Redemption
AOC 2028: : The Future of American Progressivism

Mamdani win freaks out some Dems about their own primaries

Progressive Rep. Ro Khanna (D-Calif.) told Axios "there was a wake-up-call and a shot across the bow to the establishment and the old guard" with Mamdani's win.https://t.co/0C3wS9wTBO
— Victor Narro (@NarroVictor) June 29, 2025

Thursday, June 26, 2025

Why Apple-Perplexity Merger Would Be Nearly Impossible (And Maybe a Mistake)

Why Apple-Perplexity Merger Would Be Nearly Impossible (And Maybe a Mistake)

In the history of tech, a few near-miss acquisition stories have become legend. Yahoo passed on buying Google for $1 million. Years later, it tried to buy Facebook for $1 billion. Facebook, wisely, said no. Had it said yes, Facebook likely wouldn’t exist today as we know it. Big fish don’t always know what to do with the more nimble, visionary minnows they try to swallow.

Now, a similar narrative is taking shape—only this time, the stakes are far higher. Rumors or speculation around Apple acquiring Perplexity AI—for a price that could top $200 billion—are swirling among analysts and insiders. But even if Apple could afford it, the real question is: Should it?

The answer, on multiple fronts, is likely no.

1. Mismatch of Cultures and Visions

Apple is a design-first, hardware-dominated, tightly integrated ecosystem company. Its product lifecycles are measured in years. Its DNA is secrecy, perfectionism, and control.

Perplexity, on the other hand, is a high-speed AI-native startup. Its core value lies in openness, information flow, and decentralization. It's building something more akin to an AI-infused, real-time knowledge engine for the internet. It iterates rapidly and is redefining what search, learning, and even cognition look like in a post-Google era.

Merging these two would be like trying to graft a hummingbird's wings onto an elephant. Even if the elephant pays $200 billion for those wings, it still won’t fly.

2. AI Breaks Silos — Apple Reinforces Them

AI-native companies like Perplexity aim to dissolve traditional silos—between apps, between knowledge domains, between user and machine. In contrast, Apple thrives by maintaining carefully walled gardens. From the App Store to iCloud to iMessage, Apple monetizes control.

That fundamental misalignment would make integration difficult, if not self-destructive.

An AI like Perplexity wants to answer everything, connect everything, go everywhere. Apple wants everything to go through Apple.

3. Without Leadership Transfer, It’s DOA

Let’s imagine Apple does buy Perplexity for $200 billion. If it doesn’t hand over a significant degree of operational autonomy—or better yet, elevate the Perplexity CEO to a top Apple leadership role—then it risks smothering the very magic it paid for.

You can’t buy vision, and you certainly can’t tame it. If Perplexity is absorbed into Apple as just another feature, like Siri once was, it will go the way of MySpace after its acquisition—stagnant and irrelevant. The deal would only make sense if Apple were ready to transform itself into an AI-native company and let Perplexity lead that transformation. But there's no indication Apple is even thinking that way.

4. Timing and Trajectory Matter

When Yahoo tried to buy Facebook, it was still the dominant portal. Facebook was growing but still small. Today, Perplexity is on the rise. It’s not a mature, stagnant startup looking for an exit. It's at the early stages of a trajectory that could reshape how we interact with knowledge entirely.

Selling to Apple now would cap its potential—both in market value and world impact. $200 billion may look tempting, but in the AI era, platforms that become the new internet interface might be worth trillions.

Why sell to a hardware company whose AI track record is—let’s be honest—lackluster?

Conclusion: Some Marriages Just Shouldn't Happen

The potential Perplexity brings to the table is too important, too expansive, and too transformative to be folded into Apple’s conservative, hardware-bound future. Unless Apple is willing to completely reinvent itself and hand the reins to AI-native leadership, such a merger would likely end in regret.

It wouldn’t be a strategic acquisition—it would be a slow-motion funeral for a company that might otherwise lead the next era of human-computer symbiosis.

Better idea? Let Perplexity keep flying. Let Apple keep building its walls. The future will reward the company that opens the most doors.

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Yahoo once tried to buy Facebook for $1B. Facebook said no—and changed the world.
Now whispers suggest Apple might eye Perplexity AI for $200B. But this deal, if real, would be nearly impossible—and maybe a terrible idea. Here's why 🧵@perplexity_ai @_Faraz @AravSrinivas
— Paramendra Kumar Bhagat (@paramendra) June 26, 2025

Perplexity Price: 200B For Apple. Bonus: CEO

Wednesday, June 25, 2025

ChatGPT for Robotics, Physical AI

Beyond Motion: How Robots Will Redefine The Art Of Movement

Building ChatGPT for robotics—or, more broadly, achieving Physical AI—is one of the most ambitious frontiers in artificial intelligence. It involves taking the power of LLMs like ChatGPT and embedding it into robots that perceive, act, and reason in the physical world.

Here’s a breakdown of the core challenges, current state, and realistic roadmap:

🧠 What Is Physical AI?

Physical AI refers to the fusion of:

Language models (like ChatGPT)
Embodied agents (robots)
Multimodal perception (vision, touch, audio)
Real-time actuation and control

Think: a humanoid robot you can talk to, that understands your intent, perceives its environment, and physically performs tasks—cleaning, cooking, caregiving, and more.

🚧 Core Challenges in Building ChatGPT for Robotics

1. Grounding Language in Reality

ChatGPT understands language abstractly, but robots must ground words like “grab the red cup” in sensor data.
Challenge: Matching symbolic language to real-world objects, locations, and context.

2. Perception and Multimodal Fusion

Robots need advanced 3D vision, audio recognition, force feedback, etc.
Challenge: Fusing and interpreting noisy, real-time sensory data. Cameras lie. Hands slip.

3. Action Planning and Control

Saying "set the table" is easy. Doing it means:
- Finding the plates
- Navigating around obstacles
- Using arms with dexterity
Challenge: High-dimensional planning, reinforcement learning, dynamic environments.

4. Real-Time Processing

Unlike text-only AI, Physical AI has strict latency constraints.
Robots must react in milliseconds—not seconds.
Challenge: Real-time inference on-device, or low-latency edge-cloud hybrid systems.

5. Safety and Uncertainty

Robots can cause real harm.
Challenge: Safe exploration, fail-safes, uncertainty-aware decision making.

6. Scalability and Cost

Training robots is slow and expensive.
Challenge: Data scarcity, real-world reinforcement learning is brittle and dangerous.

7. Embodiment Diversity

Every robot is different. Unlike software, there's no standard “hardware.”
Challenge: Generalizing across platforms and tasks (sim2real transfer).

🚗 How Close Are We to Self-Driving Cars?

✅ 80% Done, 80% to Go Problem

Cars like Tesla, Waymo, and Cruise handle most highway or mapped urban driving.
But the last 10-20% of edge cases—weird weather, aggressive drivers, unusual intersections—are insanely hard.
Elon Musk’s “2 years away” promise has been repeated for a decade.

Current status:

Waymo/Cruise: Limited, geofenced driverless rides.
Tesla: Level 2-2.5 autonomy (driver must monitor).
Full Level 5 (anywhere, anytime, no driver): At least 5–10 years away at scale.

🏠 What About Humanoid Robots for the Home?

2023–2025 Milestones:

Tesla Optimus, Figure 01, Agility Digit, Sanctuary AI: Early humanoid prototypes walking, lifting, using basic tools.
Some have LLM brains (like OpenAI/Grok in Figure).

Current Capabilities:

Walk, talk, pick up objects, follow simple commands.
Tasks: folding laundry, fetching items, surveillance, manufacturing support.

Major Gaps:

Dexterity (hands still clumsy)
Long-horizon planning (multi-step reasoning)
Affordability (units cost $50K+ minimum)
Adaptability (easily confused in unstructured homes)

🔮 Realistic Roadmap: When Will Physical AI Work?

Year	Milestone
2025–2027	Household robots for narrow tasks (cleaning floors, surveillance, receptionist)
2028–2030	Assistive humanoids in structured environments (elder care, warehouse support)
2030–2035	Versatile home assistants for middle-class homes; robots that cook, clean, converse
2035+	Self-driving cars and humanoid robots that can operate in unstructured public settings

💡 What’s Needed to Get There?

Sim2Real Transfer: Better simulation-to-reality pipelines (e.g., NVIDIA Isaac, Mujoco, Unity)
Multimodal foundation models: Combining vision, language, touch, motion (like Google’s RT-2, OpenAI’s VPT, DeepMind’s Gato)
Real-world data at scale: “Robot self-play” (see Google’s Robotic Transformer)
Cheap, robust humanoids: Tesla, Figure, and Sanctuary are racing to build iPhone-for-robots

🧠 Bottom Line

ChatGPT for Robotics = ChatGPT + Eyes + Ears + Hands + Legs + a brain that understands cause and effect in the real world.

We’re getting there—but it’s like building a child that not only learns language, but can do chores, survive traffic, and wash the dishes. A humanoid GPT-powered assistant in your home? Feasible in the next 5–10 years, but it will start with rich households and narrow capabilities.

1/
🤖 How do you build ChatGPT for robotics? What are the real challenges of Physical AI?
Let’s break it down: what’s possible today, what’s holding us back, and how close we are to self-driving cars and household humanoids.

🧵👇 @adcock_brett @elonmusk @Figure_robot
— Paramendra Kumar Bhagat (@paramendra) June 25, 2025

Pages

Thursday, July 10, 2025

Top 10 Most Mentioned Technology and Business Stories (July 1–10, 2025)

Top 10 Most Mentioned Technology and Business Stories (July 1–10, 2025)

1. Nvidia Surpasses $4 Trillion Market Valuation

2. Elon Musk’s xAI Launches Grok 4 Amid Antisemitism Fallout

3. Microsoft Unveils $4 Billion AI Education Initiative

4. Tesla Pursues Certification for Robotaxi Service in Arizona

5. Amazon Eyes New Multibillion-Dollar Investment in Anthropic

6. OpenAI Reportedly Merges with Product.io; GPT-5 Delayed

7. Google Research Launches MedGemma 27B Multimodal for Healthcare

8. Microsoft Saves $500M Through AI-Driven Job Cuts

9. Meta Poaches Top AI Talent from OpenAI and Apple

10. Gmail Adds “Manage Subscriptions” Feature

Notes and Observations

Monday, July 07, 2025

Multi-Disciplinary Approaches Will Win the Future

Beyond Technology Intersections

Rwanda and the Geography of Innovation

Spirituality and Corporate Culture

AI Safety Demands Enlightened Collaboration

The New Playbook for Impact

Toward a Human-Centered Future

तकनीकी संगम से आगे सोचें

रवांडा और नवाचार का भूगोल

अध्यात्म और कॉर्पोरेट संस्कृति

AI सुरक्षा के लिए वैश्विक सहयोग ज़रूरी

नए युग के लिए नई सोच

मानव-केंद्रित भविष्य की ओर

Monday, June 30, 2025

30: Sam Altman

Sunday, June 29, 2025

29: Peter Thiel

Thursday, June 26, 2025

Why Apple-Perplexity Merger Would Be Nearly Impossible (And Maybe a Mistake)

1. Mismatch of Cultures and Visions

2. AI Breaks Silos — Apple Reinforces Them

3. Without Leadership Transfer, It’s DOA

4. Timing and Trajectory Matter

Conclusion: Some Marriages Just Shouldn't Happen

Wednesday, June 25, 2025

ChatGPT for Robotics, Physical AI

🧠 What Is Physical AI?

🚧 Core Challenges in Building ChatGPT for Robotics

1. Grounding Language in Reality

2. Perception and Multimodal Fusion

3. Action Planning and Control

4. Real-Time Processing

5. Safety and Uncertainty

6. Scalability and Cost

7. Embodiment Diversity

🚗 How Close Are We to Self-Driving Cars?

✅ 80% Done, 80% to Go Problem

Current status:

🏠 What About Humanoid Robots for the Home?

2023–2025 Milestones:

Current Capabilities:

Major Gaps:

🔮 Realistic Roadmap: When Will Physical AI Work?

💡 What’s Needed to Get There?

🧠 Bottom Line