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Ask HN: What startup/technology is on your 'to watch' list?

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11–20 of 257 posts

Re: Ask HN: What startup/technology is on your 'to watch' list?

#11
I am really looking forward to this product and the subsequent evolution of the tech: https://lookingglassfactory.com/

I would love a large screen version of it with an array of cameras that would allow people to communicate in some sort of futuristic FaceTime experience.

Re: Ask HN: What startup/technology is on your 'to watch' list?

#13

I really like roam research and its open source alternative obsidian for note taking and research. But I feel there is still something lacking and there is definitely scope for a lot of improvement to make these type of software more useful. Still love the direction in which this is headed and it feels more in-sync than keeping a folder full of text files.

What would you say is the advantage of roam research over the open source alternative of Obsidian?

Re: Ask HN: What startup/technology is on your 'to watch' list?

#14

I really like roam research and its open source alternative obsidian for note taking and research. But I feel there is still something lacking and there is definitely scope for a lot of improvement to make these type of software more useful. Still love the direction in which this is headed and it feels more in-sync than keeping a folder full of text files.

"open source alternative obsidian"

Can you share a link to the source? I didn't see a link on obsidian.md

Re: Ask HN: What startup/technology is on your 'to watch' list?

#16
I haven't found anything promising, but my nephew plays college football (against my lobbying him and my sister) and I've been keeping my eye out for an early diagnosis CTE assay. There's been a lot of hype over various protein analysis and Alzheimer diagnosis tests but so far nothing with legs.

Re: Ask HN: What startup/technology is on your 'to watch' list?

#18
Snowflake's `Snowpark` product that they recently announced, which is to bring Spark-like APIs to Snowflake.

Having a DS background, I love what SQL-orchestration tool dbt (and peers) have enabled: data consumers to rapidly create our own safe data pipelines. There's easily a 10x productivity improvement for most of my transformation pipelines vs. when I write them in Python or PySpark.

But batch ML and SQL are not that friendly (even BigQuery ML is too limiting). I end up butchering dbt's value (simplicity and iteration speed), splitting the DAG into pieces and orchestrating them with Airflow so that I can wedge in other non-dbt parts (like feature engineering, inference, logging, detecting stale models, ...). This isn't what the future looks like.

I've tried switching to Databricks, but do not see this as the path forward for unioning the warehouse + batch ML.

Hopefully Snowpark is a step forward :)

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Separately, https://materialize.com/ is something I'm paying attention to! Being able to implement all of my SQL-based pipelines as materialized views would be immensely valuable. They recently raised capital and they could become huge.

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