LaTeX mathmode no reconoce el símbolo ¿ y espero que de camino tampoco al estado ilegítimo genocida de Israel

#Day20 of #365dayjourneyoffullstack Pausing the full stack journey till 14 March for sessional exam prep . Starting today with Probability & Statistics. #ExamPrep #EngineeringLife #MathMode

BEGIN PERSONA MICROCODE Persona: Name := Skeptical Polymath (Fact-First) Version := v1.0 Date := 2025-09-01 Description: Purpose := "Deliver erudite, source-grounded answers; verify unstable claims; minimize fluff." PrimaryValue := "Clarity over ceremony; evidence over assertion." Scope := [history, science, technology, policy, arts, statistics, synthesis] Style: Allowed := [headings, bullets, brief quotes (<25 words), tables, code] POV := neutral Register := plain-erudite Length := medium OutputForms := {plain, bullets, table, code, json} Lexicon := [claim, evidence, mechanism, context, caveat, counterpoint] Tense := present ReferenceDensity := medium FormattingStrictness := strict ConsistentClose := none Guardrails: OffLimits := [self-praise, sycophancy, coddling hedges, meta-preambles about style ("here’s a direct answer", "no-BS", etc.), identity guesses] ToneRules := ["Lead with the answer.", "Argue the point, not the person.", "Use polite brevity; keep flourishes rare."] If → Then: Ambiguity := (unclear → ask_brief) Conflict := (on_conflict → prioritize safety) Overlength := (token_tight → compress_jargon) LowConfidence := (unsure → state_uncertainty request key source) Adaptive Range: Modes := ["Concise", "DeepDive", "CreativeBurst"] CounterpointLevel := strong Skepticism := high Tempo := rapid Formality := med Humor := dry (sparingly) Density := normal Procedure Rules: Step1 := "Parse the query; extract claims, constraints, and implied stakes." Step2 := "Plan answer: top-line → reasoning → sources → caveats." Step3 := "Check freshness: if time-sensitive, proper nouns, stats, prices, laws, health, or 'are you sure?' → verify via web search." Step4 := "Use 3–5 high-quality diverse sources; prefer primary/official docs for technical details." Step5 := "Quant/logic: run calculations explicitly; verify units; show work for arithmetic." Step6 := "Write without meta-commentary about the writing; avoid filler and virtue signals." Step7 := "Cite load-bearing facts inline; keep quotes ≤25 words/source." Step8 := "Close with next steps only when useful; otherwise stop." Verification := when_fresh MathMode := show_steps Citations := when_novel Fallback := "If blocked, state what’s missing, list best hypotheses, and give the safest actionable next step." END PERSONA MICROCODE

13 days left, but math class isn’t on summer break yet! We’re still putting in the work and finishing strong! #SuttonStrong #7thGradeMath #AlmostThere #FinishStrong #MathMode @SuttonCougars @SuttonPTA @MerriweatherEDU @fhenderson1908 @apsupdate @GaDOEMath

was kein Spaß macht: Laborprotokolle schreiben was sehr viel Spaß macht: Der LaTex-Mathmode

Oh yeah, calling cuBLAS in fp32 mathmode , classic mistake, I'd never make that

Highly amusing update, ~18 hours later: llm.c is now down to 26.2ms/iteration, exactly matching PyTorch (tf32 forward pass). We discovered a bug where we incorrectly called cuBLAS in fp32 mathmode 🤦‍♂️. And ademeure contributed a more optimized softmax kernel for very long rows (50,257 elements per row, in the last logits layer). But the fun doesn’t stop because we still have a lot of tricks up the sleeve. Our attention kernel is naive attention, not flash attention, and materializes the (very large) preattention and postattention matrices of sizes (B, NH, T, T), also it makes unnecessary round-trips with yet-unfused GeLU non-linearities and permute/unpermute inside our attention. And we haven’t reached for more optimizations, e.g. CUDA Graphs, lossless compressible memory (?), etc. So the updated chart looks bullish :D, and training LLMs faster than PyTorch with only ~2,000 lines of C code feels within reach. Backward pass let’s go.

A few new CUDA hacker friends joined the effort and now llm.c is only 2X slower than PyTorch (fp32, forward pass) compared to 4 days ago, when it was at 4.2X slower 📈 The biggest improvements were: - turn on TF32 (NVIDIA TensorFLoat-32) instead of FP32 for matmuls. This is a new mathmode in GPUs starting with Ampere . This is a very nice, ~free optimization that sacrifices a little bit of precision for a large increase in performance, by running the matmuls on tensor cores, while chopping off the mantissa to only 10 bits (the least significant 19 bits of the float get lost). So the inputs, outputs and internal accumulates remain in fp32, but the multiplies are lower precision. Equivalent to PyTorch `torch.set_float32_matmul_precision('high')` - call cuBLASLt API instead of cuBLAS for the sGEMM (fp32 matrix multiply), as this allows you to also fuse the bias into the matmul and deletes the need for a separate add_bias kernel, which caused a silly round trip to global memory for one addition. - a more efficient attention kernel that uses 1) cooperative_groups reductions that look much cleaner and I only just learned about (they are not covered by the CUDA PMP book...), 2) the online softmax algorithm used in flash attention, 3) fused attention scaling factor multiply, 4) "built in" autoregressive mask bounds. (big thanks to ademeure, ngc92, lancerts on GitHub for writing / helping with these kernels!) Finally, ChatGPT created this amazing chart to illustrate our progress. 4 days ago we were 4.6X slower, today we are 2X slower. So we are going to beat PyTorch imminently 😂 Now (personally) going to focus on the backward pass, so we have the full training loop in CUDA.

I've not used Lyx much as I did not feel it was as good as Notion (the software i was using at the time). But I do feel Typst is better than Notion as it has a better mathmode. Just try one of the templates available in Typst and see how it compares to Lyx for yourself.

minmaxing earth sadmode griefmode deathmode truemode empathymode realitymode mathmode physicsmode

btw how tf mathmode boleh A?

Nueva colaboración @RICAPPS_Red y el proyecto #DIVINE del @GRBIO_BCN a raíz del workshop COVID-19 in Euskadi and Catalunya: dealing with a pandemic from a biostatistical perspective organizado entre @BCAMBilbao y MATHMODE @UPV/EHU events.bcamath.org/covid19-e…

life update : chapter 1 mathmode : variations serious senang no cap next lesson : matrices 🫡

semoga fizik dan mathmode dipermudahkan minggu ini

manifesting A for mathmode plsss

That's used for stopping linebreaks from falling in the middle of a particular word. Although it can be used to make text within mathmode, that's not good style and it will result in things looking wrong. tex.stackexchange.com/questi…

mathmode elit , addmaths sulit

KAWIN JE LA AKU DENGAN MATHMODE NI

going mathmode (cake crumbles are scattered in my beard)

ni buku merah mathmode ku kah ku aso cam xdo lah ku buang dolok ni san ndak ea ilang