cosgrove

In case anyone is wondering, here is the proposal from Cloudflare: https://blog.cloudflare.com/saas-to-saas-security/

TL;DR: visibility and control for all connections (marketplace apps, 4th parties) to your 3rd party SaaS platforms. See which connections are active as well as when and how much they transmit. Transparent token splitting to force connections through the proxy as well as instant token revocation and ACLs.

We are currently building this and would appreciate your feedback!

Can they really do it? Tesla is making steady progress and has reached a few new milestones recently.

They recently launched their Robotaxi service in Austin, and it seems to be as good as Waymo or better. https://youtu.be/RcaBZenrCCs

They also recently autonomously delivered a car to a customer’s apartment straight from the factory line. https://youtu.be/lRRtW16GalE

I feel like his follow up tweet was good context: https://x.com/pariljain/status/1790500423327191169?s=46

Had a great productive chat with @elonmusk before leaving, would’ve stuck around longer if I didn’t have the itch to chase a specific vision.

Don’t see any capacity eroding on his front like the article mentions

This is nice to hear about. Can you tell me more about how your live results matched or diverged from your backtesting?

Did you list the returns of the commodities as a comparison, or are you trading those futures as well in the mix? (I know you only talked about ES/MES)

but I’m more so pushing back on the added cost and complexity of human elements NOT required by the built environment

Am I understanding you correctly that you would want something that still had cameras at head height, but simply didn't have the head form factor? And perhaps had 4 arms for some tasks that it would benefit from instead of being limited to two arms?

If so, how many environments are you going to build robots for? And how does your total overall build cost increase with each different model you build?

Doesn't matter if it's simper in the end-design if getting there ends up costing you as much as it would to build a general purpose design in the first place.

Knowing starting battery temperature would go a long way to interpreting the results here. You could assume they all started the same, but it would be nice to know for sure.

Nowhere do they describe initial starting conditions for the batteries / vehicles besides saying 10% SOC at start.

I was surprised at how similar the new 15 Pro looks and feels to the 11 Pro I used to carry. I also miss the gold color way of the 13 Pro.

r/WallStreetBets folks do this type of thing all the time... wouldn't be surprised if it was someone gambling.

But if you're a paid subscriber you can access GPT4 through ChatGPT's interface. Are you saying there's a difference between using the GPT4 model alone vs. the GPT4 model in the ChatGPT interface? If so, could you please clarify with an example?

I think it's neat that they did all these studies on feasibility and projected a start date into the 2000s.

Also neat that we ended up with complimentary energy generation and storage technologies to fix the "it gets dark at night" problem of solar electricity generation!

No doubt, they are growing fast! And naturally they would make more than Tesla, since BYD makes more than just BEVs.

BYD's numbers often contain plugin hybrids (PHEV). So if you're trying to compare apples/apples, be sure to look at pure-battery EVs between the two.

Note 'electrified' from a different article from Barrons: "BYD delivered 206,089 electrified passenger vehicles in March [2023], up about 98% from the 104,338 delivered in March 2022. The March 2023 figures include 102,670 all battery electric vehicles and 103,419 plug-in hybrid models."

Hey, thanks for the detail here. Are you modeling in the increased IV due to upcoming earnings announcements? Do you hold anything in its run-up to earnings or through an earnings announcement?

Are you using OptionNet Explorer or OptionVue, or just your own software using the math you learned from your CBOE friend?

Interesting to hear about trying to use the Kelly criterion. I've always thought of it for bet sizing, which is tough since you never know your true odds (unlike counting cards, for instance).

For my own trading, I am having moderate success with selling premium on index options. I find it tough to make a meaningful amount of money while keeping blow-up risk low.

Not quite what you asked, but there was someone who did a "brain transplant" recently: https://www.tomshardware.com/news/ibm-thinkpad-701c-receives...

Short seller seems to have a pretty sober take on the reality of it all.

Reminds me of "just don't fucking dance." https://www.youtube.com/watch?v=7eYcWpgCb7o

What is your general approach? Selling premium? Earnings announcements?

Do you frequent any online communities of professionals, or is it just you, your spouse, and your mentors?

Beyond wanting to learn alternative approaches myself, I help moderate a local trading group. We are always looking for presenters in our monthly meetings.

And it wasn’t just players: autonomous mobile objects (mobs) like monsters, animals, and NPCs could cross them as well.

Started playing MMOs in 2001 and it wasn't until this day that I learned why they were called mobs. Wow.

Get a Model Y instead of a Model 3 if you can swing it and don't mind the crossover platform vs. sedan. The number of parts in a Model Y is even less than a 3 due to the gigacastings. Plus: hatchback! Who doesn't love a hatchback?

Did you see the part where the single Tesla actuator was lifting the piano up and down?

Here's a good thread about Optimus vs. Atlas: https://twitter.com/EzerRatchaga/status/1576140275847610369

Interestingly absent is a discussion about bots abusing these booking systems. GDS' usually have a look-to-book ratio threshold with their airline customers. If the airline (via end users and bots on its website) does too many computationally intensive searches without booking a flight, that airline pays overages per their contract with the GDS.

You can imagine how a third party entity would make constant searches for seat and flight availability, spurred by all the possible permutations of airports and flight schedules. This flurry of activity rockets up the number of "looks" to the number of actual "books".

These third parties might be Online Travel Agencies trying to get around their own contractual limits with the GDS, or it might be companies that sell the schedule and fare data as competitive intelligence.

For now, the GDS' and airlines try to solve the problem with anti-bot solutions to keep contractual overages low.

If someone could instead solve the underlying structural problem (computational intensity? cost of compute? cost of running a GDS? offer free fare and schedule data to all?), they could probably crack open a multi-million dollar market opportunity.

It sounds like they cater specifically to "the aural and visually impaired", but I can't figure out how?

Supposedly started with this study from 1978: https://www.semanticscholar.org/paper/Kinetics-of-the-parall...

Note that they mentioned the investment must be executable as well. Straightforward to find something to buy, but might be hard to convince the owners to sell.

Do you have goals bigger than $100/year? If so, are you hitting those goals? If you aren't achieving your goals, YNAB can help.

I knew I wasn't achieving the goals I had with my DIY spreadsheet and mint.com, and once I started using YNAB everything came together very nicely.

I'm currently on sabbatical, and I'm thinking about changing careers away from cybersecurity sales engineering and towards a career with cultivated meat. I have no biology background. Vincent, how did you prepare for this endeavor? Did you go back to school? If so, at what level and for how long?

I would relish the chance to dive into a new technical field using my existing sales skills with tons of new on-the-job training, but it feels like too much hubris on my side to go without any schooling background. Help me connect the dots, please?

As someone who has never had to truly live through a disaster (knock on wood), I found this story to be compelling in thinking about disaster planning: http://www.theplacewithnoname.com/blogs/klessons/index.html

On August 29, 2005, Hurricane Katrina became the largest natural disaster in United States history. After the levees failed, it became the largest man-made disaster in United States history. This blog is a chronicle of what happened to myself and my family during those events. It is also a documentation of lessons learned from a survival and recovery viewpoint.

I think it delivers a lot more backstory on what happens when you don't prepare for something, which you don't get simply reading a how-to list.