Articles for category: AI Tools

March 14, 2025

ikayaniaamirshahzad@gmail.com

Five New Thinking Styles for Working With Thinking Machines

Sponsored By: Bessemer Venture Partners This essay is brought to you by Bessemer Venture Partners, a leading venture capital firm investing in artificial intelligence. Discover how AI is transforming industries and creating new entrepreneurial opportunities with their latest free ebook, Everything, Everywhere, All AI. Dive into strategies and real-world case studies that will help you stay ahead of the AI revolution. Ready for the AI era? Was this newsletter forwarded to you? Sign up to get it in your inbox. A world with thinking machines requires new thinking styles.  Our default thinking style in the West is scientific and rationalist.

March 14, 2025

ikayaniaamirshahzad@gmail.com

Apple’s Siri Chief Calls AI Delays Ugly and Embarrassing, Promises Fixes

Apple’s Siri Chief Calls AI Delays Ugly and Embarrassing, Promises Fixes (via) Mark Gurman reports on some leaked details from internal Apple meetings concerning the delays in shipping personalized Siri. This note in particular stood out to me: Walker said the decision to delay the features was made because of quality issues and that the company has found the technology only works properly up to two-thirds to 80% of the time. He said the group “can make more progress to get those percentages up, so that users get something they can really count on.” […] But Apple wants to maintain

March 14, 2025

ikayaniaamirshahzad@gmail.com

Beautiful dashboards in Python with first-class real-time integration

from deephaven import ui, agg, empty_tablefrom deephaven.stream.table_publisher import table_publisherfrom deephaven.stream import blink_to_append_onlyfrom deephaven.plot import express as dxfrom deephaven import updateby as ubyfrom deephaven import dtypes as dhtstocks = dx.data.stocks().reverse()def set_bol_properties(fig): fig.update_layout(showlegend=False) fig.update_traces(fill="tonexty", fillcolor='rgba(255,165,0,0.08)')@ui.componentdef line_plot( filtered_source, exchange, window_size, bol_bands): window_size_key = { "5 seconds": ("PriceAvg5s", "PriceStd5s"), "30 seconds": ("PriceAvg30s", "PriceStd30s"), "1 minute": ("PriceAvg1m", "PriceStd1m"), "5 minutes": ("PriceAvg5m", "PriceStd5m")} bol_bands_key = {"None": None, "80%": 1.282, "90%": 1.645, "95%": 1.960, "99%": 2.576} base_plot = ui.use_memo(lambda: ( dx.line(filtered_source, x="Timestamp", y="Price", by="Exchange" if exchange == "All" else None, unsafe_update_figure=lambda fig: fig.update_traces(opacity=0.4)) ), [filtered_source, exchange]) window_size_avg_key_col = window_size_key[window_size][0] window_size_std_key_col = window_size_key[window_size][1] avg_plot = ui.use_memo(lambda: dx.line(filtered_source, x="Timestamp",

March 14, 2025

ikayaniaamirshahzad@gmail.com

Data Machina #252 – Data Machina

Diffusion, FM & Pre-Trained AI models for Time-Series. DeepNN-based models are starting to match or even outperform statistical time-series analysis & forecasting methods in some scenarios. Yet, DeepNN-based models for time-series suffer from 4 key issues: 1) complex architecture 2) enormous amount of time required for training 3) high inference costs, and 4) poor context sensitivity. Latest innovative approaches. To address those issues, a new breed of foundation or pre-trained AI models for time-series is emerging. Some of these new AI models use hybrid approaches borrowing from NLP, vision/ image, or physics modelling, like: transformers, diffusion models, KANs and state

March 14, 2025

ikayaniaamirshahzad@gmail.com

Gemma 3: What You Need To Know

Gemma 3 represents Google’s approach to accessible AI, bridging the gap between cutting-edge research and practical application. While the Gemini family represents Google’s flagship, closed, and most powerful models, Gemma offers a lightweight, “open” counterpart designed for wider use and customization. Specifically, Gemma 3’s model weights are openly released, allowing developers to download, deploy, and fine-tune the models on their own infrastructure – a significant contrast to closed models accessible only via APIs. This open-weight approach, though subject to Google’s usage license (requiring attribution and prohibiting distillation for training other models), provides far greater flexibility for teams to integrate and

March 14, 2025

ikayaniaamirshahzad@gmail.com

Evaluating the Effectiveness of LLM-Evaluators (aka LLM-as-Judge)

LLM-evaluators, also known as “LLM-as-a-Judge”, are large language models (LLMs) that evaluate the quality of another LLM’s response to an instruction or query. Their growing adoption is partly driven by necessity. LLMs can now solve increasingly complex and open-ended tasks such as long-form summarization, translation, and multi-turn dialogue. As a result, conventional evals that rely on n-grams, semantic similarity, or a gold reference have become less effective at distinguishing good responses from the bad. And while we can rely on human evaluation or finetuned task-specific evaluators, they require significant effort and high-quality labeled data, making them difficult to scale. Thus,

March 14, 2025

ikayaniaamirshahzad@gmail.com

The Power of Cooperation: Teaming Up with Different Creators

In the dynamic world of bass music, partnership is an essential part of the process; it’s an important factor for achievement. As the genre continues to progress, producers are finding that teaming up with others can open up new creative possibilities and help them make a mark in an increasingly crowded scene. Whether you are an emerging artist or a seasoned pro, partnering with fellow producers can provide new viewpoints, innovative techniques, and essential understandings that redefine your sound. With the ideal collaborations, you can discover diverse musical ideas, collate production techniques, and even address the difficulties of the industry

March 14, 2025

ikayaniaamirshahzad@gmail.com

AWS Glue Crawler: A Complete Setup Guide – BMC Software

In this tutorial, we discuss what a crawler is in Amazon Web Services (AWS), and show you how to make your own Amazon Glue crawler. A fully managed service from Amazon, AWS Glue handles data operations like ETL (extract, transform, load) to get the data prepared and loaded for analytics activities. Glue can crawl S3, DynamoDB, and JDBC data sources. What is a crawler? A crawler is an automated software app that “crawls” through the content of web pages, following the links on those pages to find and crawl additional pages. Sometimes also called spiders or bots, these software programs