“Doing NSM analysis is a demanding process and there is no mechanical procedure for it. Published explications have often been through a dozen or more iterations over several months” — (Heine, Narrog, and Goddard 2015)

Approach and XD

Introduction and Theory

The Natural Semantic Metalanguage (NSM) approach (Wierzbicka 1974) is a long-standing hypothetical theory in structural semantics which claims that all human languages share a common set of primitive lexical units—usually words, but, in some languages, short connected phrases—through which all other words in each language can be defined.

NUS Secondary School Other Duties

• AP Statistics Index
• AP Phys C Mech Index
• AP Phys C EM Index
• Tuning Forks
• bioinformatics
• PKM
• Intersession 2023

NUS-MATH580 QIC

NUS-CS223 Algorithms

Backlog: Finite State Machine

NUS-HIST301 American History

Backlog: New Deal, Franklin D. Roosevelt (FDR), Works Progress Administration, effects of the New Deal, Great Depression, Herber Hoover, disinformation, Guilded Age

Let’s begin. We want to create test for the linearity of a few assets, for whether or not they follow the CAPM.

Note that we will be using the Sharpe-Linter version of CAPM:

\begin{equation} E[R_{i}-R_{f}] = \beta_{im} E[(R_{m}-R_{f})] \end{equation}

\begin{equation} \beta_{im} := \frac{Cov[(R_{i}-R_{f}),(R_{m}-R_{f})]}{Var[R_{m}-R_{f}]} \end{equation}

Recall that we declare \(R_{f}\) (the risk-free rate) to be non-stochastic.

Let us begin. We will create a generic function to analyze some given stock.

We will first import our utilities

TPU Topo

HBM renders into two memories: vmem, where matricies go, and smem, where scalars and conditional logic goes.

Recall that math happens in vmem.

OG Pallas

1. memory pipelining: HBM and VMEM mapping between
2. custom prefetch: PrefetchScalarGridSpec—enable runtime dependent scalar transform
3. input-output aliasing: recycle input and output buffers for in-place updates
4. passing HBM buffers: for collectives where there’s no real math etc., you can just pass references to HBM

pl.kernel

A brand new API. Also need multi-core support like Megacore stuff.

Introduction

Recent advances of language models (LMs) introduced the possibility of in-context, few or zero-shot reasoning (Brown et al. 2020) using LMs without much or any fine tuning.

Yet, classically, LM decoding takes place in a left-to-right fashion, auto-regressively resolving one token at a time by sampling from the output distribution of possible next words without multi-step planning.

Work in LM agents have taken steps to solve more complex problems that would typically require multi-step reasoning even while using this direct decoding approach. The simplest idea, named “chain-of-thoughts” (CoT), involves forcing the LM at decode time to begin the decoding process with natural language reasoning about its actions (Wei et al. 2022). The method has contributed to the creation of powerful language agents (Yao, Zhao, et al. 2023) that can reason about complex actions.