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Navigating the First AI Winter: Lessons from Asia’s Artificial Intelligence History

The first AI winter (1974-1980) was a challenging period for AI research, marked by reduced funding and interest. This article explores the causes, impact, and key figures of this era and its lessons for the future of AI and AGI in Asia.

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First AI winter

TL;DR:

  • The first AI winter (1974-1980) was a period of reduced funding and interest in artificial intelligence research due to overhyped expectations, technical limitations, and critical reports.
  • Key figures like Marvin Minsky, James Lighthill, and Herbert Simon played significant roles during this period, shaping the trajectory of AI research.
  • The AI winter had profound effects on the field, but some researchers continued to make progress, leading to a more focused approach to AI research.

The First AI Winter: A Historical Overview

Artificial intelligence (AI) has come a long way since its inception, with numerous advancements shaping the technological landscape. However, the journey has not been without its challenges. The first AI winter, spanning from 1974 to 1980, marked a significant period of reduced funding and interest in AI research. This downturn followed an era of high expectations and optimism in the 1950s and 1960s, when researchers made bold predictions about AI’s potential. The winter was triggered by a combination of factors, including overhyped expectations, technical limitations, and critical reports like the Lighthill Report, which questioned the field’s progress and led to funding cuts.

Causes of the First AI Winter

The first AI winter was caused by several factors that led to reduced funding and interest in artificial intelligence research:

  1. Overhyped expectations: Early AI researchers made ambitious predictions about AI capabilities that failed to materialize, leading to disappointment.
  2. Technical limitations: The computing power and algorithms available at the time were insufficient to solve complex real-world problems, exposing the limitations of early AI systems.
  3. Lighthill Report: This influential 1973 report criticized AI research for failing to achieve its “grandiose objectives,” leading to funding cuts in the UK.
  4. Combinatorial explosion: Researchers realized that many AI problems faced exponential growth in complexity as input size increased, making them computationally intractable.
  5. Lack of computing power: The hardware available at the time was insufficient to handle the computational requirements of many AI applications.
  6. Funding cuts: Government agencies, particularly DARPA in the US, reduced or eliminated funding for AI research.

These factors collectively contributed to a loss of confidence in AI’s potential, leading to the first AI winter.

Impact of the First AI Winter

The first AI winter had profound effects on the field, leading to a significant reduction in funding from government agencies and private investors. Many AI projects were shut down, and research activities slowed considerably. Researchers shifted their focus to other areas of computer science perceived to have more immediate practical applications. Despite these setbacks, some researchers continued to make progress, developing new ideas in areas such as logic programming and commonsense reasoning. The period also led to a more measured and focused approach to AI research, setting the stage for future advancements in the field.

Key Figures and Their Contributions

Several key figures played important roles during and around the first AI winter period:

  1. Marvin Minsky: A co-founder of MIT’s AI laboratory, Minsky contributed to early AI research but also inadvertently contributed to the winter. His 1969 book “Perceptrons” highlighted limitations of single-layer neural networks, leading to reduced interest in neural network research for over a decade.
  2. James Lighthill: A prominent mathematician who authored the influential Lighthill Report in 1973. His scathing critique of AI research’s progress significantly impacted funding and public perception of AI in the UK.
  3. Herbert Simon: An early AI pioneer who made overly optimistic predictions about AI’s capabilities, contributing to inflated expectations.

AI Research Revival

The revival of AI after the first winter was marked by several significant projects and advancements. Expert systems, machine learning, and neural networks saw renewed interest, with researchers exploring new approaches to overcome previous limitations. Additionally, the increased availability of computing power and growth in data enabled AI systems to tackle more complex problems. These projects and advancements collectively contributed to a resurgence of interest and progress in AI, effectively ending the first AI winter and setting the stage for further developments in the field.

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OpenAI’s New ChatGPT Image Policy: Is AI Moderation Becoming Too Lax?

ChatGPT now generates previously banned images of public figures and symbols. Is this freedom overdue or dangerously permissive?

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OpenAI moderation policy

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

  • ChatGPT can now generate images of public figures, previously disallowed.
  • Requests related to physical and racial traits are now accepted.
  • Controversial symbols are permitted in strictly educational contexts.
  • OpenAI argues for nuanced moderation rather than blanket censorship.
  • Move aligns with industry trends towards relaxed content moderation policies.

Is AI Moderation Becoming Too Lax?

ChatGPT just got a visual upgrade—generating whimsical Studio Ghibli-style images that quickly became an internet sensation. But look beyond these charming animations, and you’ll see something far more controversial: OpenAI has significantly eased its moderation policies, allowing users to generate images previously considered taboo. So, is this a timely move towards creative freedom or a risky step into a moderation minefield?

ChatGPT’s new visual prowess

OpenAI’s latest model, GPT-4o, introduces impressive image-generation capabilities directly inside ChatGPT. With advanced photo editing, sharper text rendering, and improved spatial representation, ChatGPT now rivals specialised image AI tools.

But the buzz isn’t just about cartoonish visuals; it’s about OpenAI’s major shift on sensitive content moderation.

Moving beyond blanket bans

Previously, if you asked ChatGPT to generate an image featuring public figures—say Donald Trump or Elon Musk—it would simply refuse. Similarly, requests for hateful symbols or modifications highlighting racial characteristics (like “make this person’s eyes look more Asian”) were strictly off-limits.

No longer. Joanne Jang, OpenAI’s model behaviour lead, explained the shift clearly:

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“We’re shifting from blanket refusals in sensitive areas to a more precise approach focused on preventing real-world harm. The goal is to embrace humility—recognising how much we don’t know, and positioning ourselves to adapt as we learn.”

In short, fewer instant rejections, more nuanced responses.

Exactly what’s allowed now?

With this update, ChatGPT can now depict public figures upon request, moving away from selectively policing celebrity imagery. OpenAI will allow individuals to opt-out if they don’t want AI-generated images of themselves—shifting control back to users.

Controversially, ChatGPT also now accepts previously prohibited requests related to sensitive physical traits, like ethnicity or body shape adjustments, sparking fresh debate around ethical AI usage.

Handling the hottest topics

OpenAI is cautiously permitting requests involving controversial symbols—like swastikas—but only in neutral or educational contexts, never endorsing harmful ideologies. GPT-4o also continues to enforce stringent protections, especially around images involving children, setting even tighter standards than its predecessor, DALL-E 3.

Yet, loosening moderation around sensitive imagery has inevitably reignited fierce debates over censorship, freedom of speech, and AI’s ethical responsibilities.

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A strategic shift or political move?

OpenAI maintains these changes are non-political, emphasising instead their longstanding commitment to user autonomy. But the timing is provocative, coinciding with increasing regulatory pressure and scrutiny from politicians like Republican Congressman Jim Jordan, who recently challenged tech companies about perceived biases in AI moderation.

This relaxation of restrictions echoes similar moves by other tech giants—Meta and X have also dialled back content moderation after facing similar criticisms. AI image moderation, however, poses unique risks due to its potential for widespread misinformation and cultural distortion, as Google’s recent controversy over historically inaccurate Gemini images has demonstrated.

What’s next for AI moderation?

ChatGPT’s new creative freedom has delighted users, but the wider implications remain uncertain. While memes featuring beloved animation styles flood social media, this same freedom could enable the rapid spread of less harmless imagery. OpenAI’s balancing act could quickly draw regulatory attention—particularly under the Trump administration’s more critical stance towards tech censorship.

The big question now: Where exactly do we draw the line between creative freedom and responsible moderation?

Let us know your thoughts in the comments below!

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Tencent Joins China’s AI Race with New T1 Reasoning Model Launch

Tencent launches its powerful new T1 reasoning model amid growing AI competition in China, while startup Manus gains major regulatory and media support.

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Tencent T1 reasoning model

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

  • Tencent has launched its upgraded T1 reasoning model
  • Competition heats up in China’s AI market
  • Beijing spotlights Manus
  • Manus partners with Alibaba’s Qwen AI team

The Tencent T1 Reasoning Model Has Launched

Tencent has officially launched the upgraded version of its T1 reasoning model, intensifying competition within China’s already bustling artificial intelligence sector. Announced on Friday (21 March), the T1 reasoning model promises significant enhancements over its preview edition, including faster responses and improved processing of lengthy texts.

In a WeChat announcement, Tencent highlighted T1’s strengths, noting it “keeps the content logic clear and the text neat,” while maintaining an “extremely low hallucination rate,” referring to the AI’s tendency to generate accurate, reliable outputs without inventing false information.

The Turbo S Advantage

The T1 model is built on Tencent’s own Turbo S foundational language technology, introduced last month. According to Tencent, Turbo S notably outpaces competitor DeepSeek’s R1 model when processing queries, a claim backed up by benchmarks Tencent shared in its announcement. These tests showed T1 leading in several key knowledge and reasoning categories.

Tencent’s latest launch comes amid heightened rivalry sparked largely by DeepSeek, a Chinese startup whose powerful yet affordable AI models recently stunned global tech markets. DeepSeek’s success has spurred local companies like Tencent into accelerating their own AI investments.

Beijing Spotlights Rising AI Star Manus

The race isn’t limited to tech giants. Manus, a homegrown AI startup, also received a major boost from Chinese authorities this week. On Thursday, state broadcaster CCTV featured Manus for the first time, comparing its advanced AI agent technology favourably against more traditional chatbot models.

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Manus became a sensation globally after unveiling what it claims to be the world’s first truly general-purpose AI agent, capable of independently making decisions and executing tasks with minimal prompting. This autonomy differentiates it sharply from existing chatbots such as ChatGPT and DeepSeek.

Crucially, Manus has now cleared significant regulatory hurdles. Beijing’s municipal authorities confirmed that a China-specific version of Manus’ AI assistant, Monica, is fully registered and compliant with the country’s strict generative AI guidelines, a necessary step before public release.

Further strengthening its domestic foothold, Manus recently announced a strategic partnership with Alibaba’s Qwen AI team, a collaboration likely to accelerate the rollout of Manus’ agent technology across China. Currently, Manus’ agent is accessible only via invite codes, with an eager waiting list already surpassing two million.

The Race Has Only Just Begun

With Tencent’s T1 now officially in play and Manus gaining momentum, China’s AI competition is clearly heating up, promising exciting innovations ahead. As tech giants and ambitious startups alike push boundaries, China’s AI landscape is becoming increasingly dynamic—leaving tech enthusiasts and investors eagerly watching to see who’ll take the lead next.

What do YOU think?

Could China’s AI startups like Manus soon disrupt Silicon Valley’s dominance, or will giants like Tencent keep the competition at bay?

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Google’s Gemini AI is Coming to Your Chrome Browser — Here’s the Inside Scoop

Google is integrating Gemini AI into Chrome browser through a new experimental feature called Gemini Live in Chrome (GLIC). Here’s everything you need to know.

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Gemini AI Chrome

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

  • Google is integrating Gemini AI into its Chrome browser via an experimental feature called Gemini Live in Chrome (GLIC).
  • GLIC adds a clickable Gemini icon next to Chrome’s window controls, opening a floating AI assistant modal.
  • Currently being tested in Chrome Canary, the feature aims to streamline AI interactions without leaving the browser.

Welcoming Google’s Gemini AI to Your Chrome Browser

If there’s one thing tech giants love more than AI right now, it’s finding new ways to shove that AI into everything we use. And Google—never one to be left behind—is apparently stepping up their game by sliding their Gemini AI directly into your beloved Chrome browser. Yep, that’s the buzz on the digital street!

This latest AI adventure popped up thanks to eagle-eyed folks at Windows Latest, who spotted intriguing code snippets hidden in Google’s Chrome Canary version. Canary, if you haven’t played with it before, is Google’s playground version of Chrome. It’s the spot where they test all their wild and wonderful experimental features, and it looks like Gemini’s next up on stage.

Say Hello to GLIC: Gemini Live in Chrome

They’re calling this new integration “GLIC,” which stands for “Gemini Live in Chrome.” (Yes, tech companies never resist a snappy acronym, do they?) According to the early glimpses from Canary, GLIC isn’t quite ready for primetime yet—no shock there—but the outlines are pretty clear.

Once activated, GLIC introduces a nifty Gemini icon neatly tucked up beside your usual minimise, maximise, and close window buttons. Click it, and a floating Gemini assistant modal pops open, ready and waiting for your prompts, questions, or random curiosities.

Prefer a less conspicuous spot? Google’s thought of that too—GLIC can also nestle comfortably in your system tray, offering quick access to Gemini without cluttering your browser interface.

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Why Gemini in Chrome Actually Makes Sense

Having Gemini hanging out front and centre in Chrome feels like a smart move—especially when you’re knee-deep in tabs and need quick answers or creative inspiration on the fly. No more toggling between browser tabs or separate apps; your AI assistant is literally at your fingertips.

But let’s keep expectations realistic here—this is still Canary we’re talking about. Features here often need plenty of polish and tweaking before making it to the stable Chrome we all rely on. But the potential? Definitely exciting.

What’s Next?

For now, we’ll keep a close eye on GLIC’s developments. Will Gemini revolutionise how we interact with Chrome, or will it end up another quirky experiment? Either way, Google’s bet on AI is clearly ramping up, and we’re here for it. Don’t forget to sign up to our occasional newsletter to stay informed about this and other happenings around AI in Asia and beyond.

Stay tuned—we’ll share updates as soon as Google lifts the curtains a bit further.

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