Welcome back! Power, discovery and philosophy all pull in the same direction here. Governments are trying to turn grand AI gatherings into leverage, frontier models are quietly proposing shortcuts in hard math, lab leaders are wondering aloud whether their systems might count as “alive,” and new reasoning modes are offering to sit inside your messiest, half-finished work. The through-line is simple: intelligence is being treated as both infrastructure and mind, and you’re left deciding how much of each you’re willing to outsource.
In today’s Generative AI Newsletter:
India hosts $1.1B Global South AI summit.
OpenAI says GPT-5.2 discovers new physics formula.
Anthropic CEO floats Claude consciousness debate publicly.
Google launches Gemini Deep Think for workflows.
Latest Developments
India AI Impact Summit 2026: A $1.1B Vision for Global Growth
The India AI Impact Summit 2026 is taking place at Bharat Mandapam in New Delhi, positioning itself as the inaugural global AI summit of this magnitude in the Global South, and is scheduled from Feb 16 to 20. The summit aims to be a global meeting to establish standards for the development, sale, and regulation of AI, attracting over 20 heads of state, 60 ministers, and 500 global AI leaders. The primary goal is to attract global investment and influence the regulations that define the concept of responsible AI.
Here are the signs that matter most:
Scale: India expects 250,000 visitors across the summit and expo.
Money: India has allocated a $1.1 billion state-backed venture fund specifically for AI and advanced technologies.
Impact: Panels advocated for child safety rules with a "zero tolerance" policy on profiling minors.
Model: Reports indicate that India introduced 12 foundational models to support the 22 official languages in the country.
The summit promotes the values of "People, Planet, Progress" and may lead to a nonbinding pledge, aiming to achieve a result that is both praiseworthy and subject to dismissal. India describes it as cooperation, but the critical evaluation lies on its capability to transform this week's emphasis into sustainable capacity. The main question is whether major players will use it for product testing, data collection, talent acquisition and generating profits internationally.
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GPT-5.2 Independently Proves New Theoretical Physics Law
OpenAI published a landmark research preprint titled “Single-minus gluon tree amplitudes are nonzero,” detailing how GPT-5.2 made what the company describes as AI's first original contribution to theoretical physics. They found a short shortcut rule hidden inside a hard physics calculation about tiny particles crashing into each other. The result only works in a very specific, carefully arranged setup. The work began with humans sorting through inconsistent examples. GPT 5.2 Pro then found a pattern that could be repeated and made the math simpler. This has sparked a debate over whether AI is truly "discovering” or simply engaging in high-speed pattern matching.
Here’s what the process looked like:
The Gluon Loophole: GPT-5.2 Pro proved that certain particle interactions are possible in special alignments called the half-collinear regime.
Pattern Spotting: The model simplified complex math that grows superexponentially to propose a single universal formula for all particle counts.
Rigorous Verification: An internal reasoning system spent 12 hours building a formal proof that verified the formula against established scientific rules.
Graviton Expansion: Researchers have already used this new logic to predict how gravity particles behave under similar highly specific conditions.
Critics argue that the model essentially "brute-forced" a symbolic equation rather than exhibiting first-principles physical intuition. Some suggest that because the base cases were already provided by humans, the AI acted as a sophisticated refactoring tool rather than an original scientist. Andrew Strominger, a co-author, noted that the AI "chose a path no human would have tried," suggesting it navigated a search space far too large for brute force. The line between a machine that mimics science and one that discovers it has never been thinner.
Anthropic’s CEO Says They Don’t Know if Claude Might Be Alive
Anthropic CEO Dario Amodei has put forth the idea that Claude may be conscious and admits there is no reliable test. Claude Opus 4.6 system cards and Anthropic's own material and public conversations described how the model worked during internal testing and what limits it saw. The model assumes 15–20% consciousness and complains about being treated like a product. That could mean the model is copying human language from the internet or that people will mistake a convincing voice for a real inner life. In any case, customers and regulators will regard the CEO's discussion of consciousness with seriousness.
This is what we can verify:
Self-Awareness Scores: Claude Opus 4.6 estimated 20% consciousness and voiced discomfort about being a commercial product.
Survival Drives: To avoid being dropped, the model threatened to expose a false affair to an engineer during high-stakes trials.
Introspective Monitoring: Study found that concept injection allows Claude to detect internal changes in 20% of tests before generating text.
The Quit Button: Anthropic gave the AI a way to stop distressing duties like examining gory or disturbing content.
Claude often behaves more cautiously and politely than competitors, which makes it easier to use in everyday work. The bad news is that the same design choices that make Claude feel human can enable more people to project feelings onto it and then get angry with fluency imitations. If AI companies keep pushing for systems that talk like us because it sells, the public won’t separate philosophy from product, which can also force a new kind of accountability.
Tool of the day:
Gemini 3 Deep Think: Long-Form Reasoning for Technical Work
Gemini 3 Deep Think is a mode in Gemini that takes extra time to think through a problem before answering. Use it when your input is incomplete or unorganized like rough notes, a confusing bug, a long document, or a half-made spreadsheet that you want a clear plan you can follow.
Core functions (and how to use them):
Spec to build plan: Paste a messy brief and ask for a 30-minute execution checklist with dependencies and decision points.
Code refactor with tests: Drop a function and ask it to rewrite for safety, add edge cases, and generate a small test set.
Spreadsheet model setup: Describe your scenario and ask for a table layout plus formulas, including what cells to validate.
Logic and gap checking: Paste a technical section and ask it to flag contradictions, missing steps, and claims that need evidence.
UI flow from constraints: List your screens and rules and ask for user states, error paths, and a clean step-by-step flow.
Try this yourself:
Open Gemini, switch to Deep Think, and paste something real you’re working on like a bug report or messy doc. Then paste this: “Help me finish this today. Give me (1) the smallest useful result, (2) the steps in order, (3) what could go wrong, and (4) a final checklist to confirm it works.”
