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!
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.
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.
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.
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?
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.
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!