Friday, July 24, 2026

Conjecture COnjecture everywhere

Conjecture about recurring digits in Pre Algebra homework

Wednesday, July 22, 2026

polynomial multiplication

polynomial multiplication · point-value swap · roots of unity · recursion · one flipped sign

prompt like a mathematician

Tuesday, July 21, 2026

Claude agents

Build with Thariq

a model trained on short tasks generalizes to problems 100x longer for free

Monday, July 20, 2026

Slack monitor

Slack probe

Here is how on-chip controllers monitor and react to degrading timing slack in real time.

1. In-Situ Slack Monitors

Instead of measuring voltage or temperature as proxies, controllers use dedicated hardware sensors embedded directly inside the critical logic paths.

Canary Circuits: Replica logic paths that mimic the slowest paths on the chip but are intentionally designed to fail slightly earlier than the actual operational logic. [1]
Razor Flip-Flops: Specialized latches that sample data twice—once at the normal clock edge and a second time slightly later. If the two samples disagree, it indicates the timing slack has shrunk to a dangerous level.
Transition Detectors: Sensors that watch data lines during a "guardband" window right before the clock edge. Any signal transition inside this window triggers a warning that slack is critically low.

2. Controller-Driven Recovery Mitigation

When the on-chip telemetry controller detects that the timing slack is nearing zero, it executes rapid hardware-level interventions:

[Slack Warning Triggered] │ ├──► 1. Clock Throttling (Immediate): Stretches or skips next clock cycle to grant more time. ├──► 2. Voltage Boosting (Transient): Signals PMIC to raise Vdd to speed up transistors. └──► 3. Architectural Re-execution: Re-runs the cycle securely if a Razor flip-flop detects a late transition.

Dynamic Frequency Scaling (DFS): The controller immediately reduces the clock frequency (stretching the cycle time) to artificially open up the timing slack.
Adaptive Voltage Scaling (AVS): The controller commands the Power Management IC (PMIC) to step up the voltage, forcing the transistors to switch faster and restoring the timing margin.
Instruction Re-execution: If a Razor flip-flop catches a late-arriving signal that missed the primary clock edge, the controller stalls the pipeline and replays the instruction using the correct, late-sampled data.

Predictive Failure Analysis

Controllers also log the frequency of these near-miss slack events. If a specific core or execution unit continuously triggers slack warnings under normal workloads, the controller flags it as aging or degraded (due to phenomena like Negative-Bias Temperature Instability, or NBTI). The system firmware can then permanently map out or down-clock that specific block to avoid permanent SDC risks.

TRANSPOSING INFORMATION USING SHADOW LATCHES AND ACTIVE LATCHES FOR EFFICIENT DIE AREA IN PROCESSING SYSTEM

Sunday, July 19, 2026

SSD

How to write to SSD

REO: Revisiting Erase Operation for Improving Lifetime and Performance of Modern NAND Flash-Based SSDs

Wednesday, July 15, 2026

negotiating in pajamas

why you should learn RL by touching nothing but the config and watching the curve go up, and why the intelligence ceiling of a specialised open-source model now subsumes the frontier for most real tasks

systemdesign concepts

Mathematical foundations of generative AI

llm compressing language

Sunday, July 05, 2026

Understanding and Answering

https://paulabartabajo.substack.com/p/how-to-pass-a-technical-interview

Knowledge Graphs, the Missing Link in Agentic AI-based Formal Verification

Agentic AI-based Coverage Closure for Formal Verification

NY story

After a red eye flight, our five year old was tired. We were meeting friends in the new york city during the layover of international travel.

When the city was just waking up on a holiday, our friend bought us breakfast from a food stand.As we were leaving with our food, the stand owner gave our toddler a donut. He refused money for it. Intended to make the kid happy but it made a strong impression on us. A welcome to the city!!

I have been to the city many times hauling back a suticase full of second hand books from The Strand Store, Times square visit that I rendered in a poem, but that donut!!

10 years later

Any parent with a kid needs to know, where the restrooms are!! Our fiend dropped us at an entrance. There were few levels in the building. The receptionist said that the closest restroom was at a place called Occ.. something.

We started running, from one way pointer to another. It was a miracle that so much running could be done with a full bladder. Finally, the apple store pointer helped. Later in the evening, we were being shown around the Occulus, which we had seen 10 years ago, and as we were walking through it, our eyes fell on the Apple store sign and my younger one and I gave out a big laugh of the place etched in our minds, coming full circle in many ways.

Saturday, July 04, 2026

Agentic AI

https://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/Archive/EECS-2016-143.pdf - GPU Latency

https://www.cmu-agents.com/

https://www.developing.dev/p/mit-complexity-theorist-on-leetcode

Sunday, June 28, 2026

MFU

The iron triangle: latency, throughput, cost

Goodput

https://github.com/stas00/ml-engineering/blob/master/training/performance/README.md

Transformer math

Training Large Language Models Pretraining, Alignment, and Scaling Modern AI

Monday, June 22, 2026

Alisa job search

https://alisawuffles.github.io/blog/job-search/

https://alisawuffles.notion.site/alisa-s-book-of-llms

https://alisawuffles.notion.site/math-notes

Thursday, June 18, 2026

Innovation by Scale

Due to the increased wealth produced by the country, the need for currency also grew. from a translated substack.

A passing thought, expounded by chatgpt.--

From Thought to Power: How Human Coordination Shapes Civilization

Someone once interpreted what I was saying as "thought is money."

What I was trying to describe was that human civilization evolves through increasingly powerful ways of organizing thought.

The human brain is remarkable because it can create models of reality. We think, imagine, plan, and solve problems. In many ways, artificial intelligence is humanity's attempt to replicate or extend that capability. AI is essentially an effort to scale cognition itself.

But once you have intelligence, another challenge immediately appears: how do you organize it?

A single mind can accomplish only so much. Civilization emerged when humans learned to coordinate many minds together. The next great step after thought was organization.

Throughout history, we have invented different systems to organize human activity.

Language allowed people to share ideas.

Writing allowed knowledge to survive across generations.

Politics emerged as a way to organize large groups of people whose interests were not always aligned.

As societies became largeranother invention transformed coordination: currency.

Before money, exchange was limited and inefficient. Currency created a common language of value. It enabled strangers to cooperate without needing personal relationships or direct barter. Wealth accumulation became possible on a scale never seen before.

Over time, the pursuit of wealth became a central organizing force in many societies. Entire economies, institutions, and governments began orienting themselves around growth, production, and capital.

Yet money itself was never the final goal. It was simply another coordination technology.

Seen through this lens, history can be viewed as a sequence of increasingly sophisticated coordination systems:

Thought coordinates perception.
Language coordinates minds.
Writing coordinates knowledge across time.
Politics coordinates populations.
Currency coordinates economic value.
Corporations coordinate labor and resources.
Computers coordinate information.
Networks coordinate the world.
Artificial intelligence coordinates cognition.

Each step expands humanity's ability to act collectively.

Today, we may be entering another transition.

For centuries, intelligence was scarce. Human expertise was limited by the number of trained people available. AI changes that equation. If cognitive capability becomes abundant, then intelligence itself may no longer be the primary constraint.

The bottlenecks shift elsewhere.

Now we hear discussions about data centers, energy production, semiconductor manufacturing, electrical grids, and geopolitical influence. These are not separate from the AI story; they are the next layer of it.

When cognition becomes easier to produce, the scarce resources become the infrastructure required to support it.

In previous eras, land was power.

Then labor was power.

Then capital was power.

Today, computation, energy, and the ability to govern complex systems may become the defining sources of power.

This is why AI discussions quickly become discussions about politics, economics, energy, and global strategy. Once intelligence can be scaled, organization becomes the central challenge again.

Perhaps the history of civilization is not primarily a story of technology, money, or governments. Perhaps it is a story of coordination.

Human thought created systems of organization. Politics organized people. Currency organized incentives. Computers organized information. AI organizes cognition.

And as cognition becomes increasingly abundant, power, energy, infrastructure, and governance become the next frontiers of human coordination.