Ollama is supercharged by MLX's unified memory use on Apple Silicon - AppleInsider
<a href="https://news.google.com/rss/articles/CBMirgFBVV95cUxNRWxucjMybjBJTHo5YWcyM2hlcE9LWFpiV05aNFhXdzYxSzk5TDlNMUpZc2NqRGY5YlpfYkxINnYtZVgtWEZHM09PelpZRDFvTlBzQWJET3BSa01WZlRxZmNVRDZYdHI5T2NBTWx0NG45ZmdzM25mbjJBbnY3dC1CMHRzU2dhQ3lHbEFwMzZxUkllNUpoRzR3Q0Y5WUJWVE5ISlhaSm4yRUZzbGo3UFE?oc=5" target="_blank">Ollama is supercharged by MLX's unified memory use on Apple Silicon</a> <font color="#6f6f6f">AppleInsider</font>
Could not retrieve the full article text.
Read on Google News: LLM →Sign in to highlight and annotate this article

Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Models
Financial News Sentiment Analyzer
Bloomberg Terminal costs $24,240/year. I built something that does the sentiment analysis part for $0.02 per article. It's not Bloomberg. It doesn't do terminal access, charting, or messaging. But if all you need is "what's the market saying about NVDA right now?", it gets you 90% of the way for 0.001% of the cost. Why I Built This I was building a trading signal pipeline and needed financial sentiment data. My options were: Pay Bloomberg $24K/year (lol no) Use Finnhub's sentiment endpoint ($500/year, but the sentiment is basic. Just positive/negative with no confidence score) Scrape it myself I went with option 3. Spent a few weeks scraping Yahoo Finance, Google News, and SEC EDGAR, wiring up VADER for quick sentiment, then an LLM for the headlines VADER gets wrong. Then I realized other
How I Made Claude Actually Reliable at Math (5-Minute Setup)
I spent a week watching Claude confidently give me wrong answers. Not wrong opinions — wrong numbers . TDEE calculations off by 200 calories. Mortgage amortization that didn't add up. Compound interest that was close-ish but not quite right. The thing is, Claude sounds confident when it hallucinates math. It walks you through the reasoning, uses the right formula names, and arrives at a number that feels plausible. The problem only shows up when you check the work. This is a known issue with LLMs. They don't actually "do math" — they pattern-match from training data. Arithmetic is surprisingly unreliable, especially for multi-step calculations. Here's how I fixed it. The Problem: LLMs Are Not Calculators When you ask Claude to calculate your TDEE (Total Daily Energy Expenditure), it might


Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!