MergeYourData.com | Data Engineer | Contract | Remote
We're looking to bring on a contractor for several projects that need assistance with data engineering and data architecture. You'll be working on GCP and AWS, and the architecture components will be determined by you and the team depending on the needs of the client.
Feel free to send an application to dan @ company name. Would be happy to share more about the specific projects, how we work, etc.
Wondering how this is going to change the remote working experience. If the price point starts coming down, I can see this as really useful for digital "in-person" meetings that keep people more engaged than a Zoom call.
Intrigued to test this device out to see if it's really much different from the typical VR experiences.
It is like a deal killer for me that in meetings that you get swapped for a creepy uncanny valley version of yourself. The hardware seemed amazing, but the software was disappointing.
Kinda silly to assume that the data is an exact reflection of reality when that link is reporting on "incidents". Especially when you can visit the city and witness stark difference compared to walking around somewhere like Miami, Houston, or New York.
Incidents are actual reports to police, not a log of all activities happening in the city. Several factors can influence reporting rates in a city, causing over or underreporting. Especially if you doubt the effectiveness and corruptibility of the police. Homicides are direct reports of victims and more accurate.
Plus, the linked article is based on the San Francisco Police Department website's crime data. Not saying that nefarious activity is the case, but has this data been audited by a 3rd party? There's definitely an incentive to show that things are better than they are if funding, elections, etc. depend on it.
Welcome to the majority of "journalism". All it takes is a look one or two levels down into the "facts" presented to realize they're wildly and poorly extrapolated to fit a narrative by whoever is paying the bills.
tuning a model to a statistical sample of the past doesn't give as much assurance about it's predictive power as people think.
then, only in the future do we find that the model failed to predict, by which time they tell us, "yeah, but we have a new model", to which the only appropriate answer is "yeah, but you had the same certainty about your old model that did not work"
I'm not saying that there's no point in modelling: you learn a lot about the dynamics of the system when you are working on the model; but that's not what the resultant model conveys.
This is less insightful then you might think, as it's not limited to modeling. We just have a tendency to use previous observations as truth for future endeavors. Mainly because it's usually fine and works fine.
You can see it in every second discussion about any topic that's currently being researched:
I.e. there is nothing guaranteeing we won't have a super viral virus with 90%+ chance of death. It could happen...
There is nothing guaranteeing that LLMs ability to output relevant data will get better, even if it's been tremendously improved within the last year alone.
You can basically see this in action whenever someone is making a prediction. The likelihood of it coming true might be good enough to work with it, but you can always have something go amiss, or a meteor out of currently unknown materials hits the sun causing a chain reaction which causes it to go supernova...
It usually isn't. John Kay and Mervyn King wrote a good book on this issue. They talk about events in three categories. Deterministic predictions, say where is the earth in five years in the solar system, probabilistic predictions based on past data, i.e. how likely is it that the volcano will explode in the next five years, and the most important one which they call 'radically uncertain' events.
Complex human events are almost always in the last category. Using the language from the first or second class of events to make predictions about completely dynamic systems that are entirely dependent on human intervention that have no clear relationship to the past makes no sense. Using quantitative language in that case is actively misleading because it creates the impression you have any notion of the total space of possible events at all. "X has a 80% of going to war in Y years" is an example. What they really mean to say is "I believe it is likely that..", but that 80% number is completely made up.
Or as Frank Knight put it: “A measurable uncertainty, or ‘risk’ proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all.”
But modeling is always a thing of probabilities, with a low confidence rating for getting it entirely right.
What you seems to have an issue with is how it's often reported on or used in politics... But the people actually creating the models are in my experience always aware that the results are never proving anything by themselves... And blaming the act of modeling for the actions of politicians and reporters is misguided, as they're just using whatever is convenient. If it wasn't a specific model, they'd find something else to validate whatever asinine bullshit they're peddling.
While the lock-in is real, there are other platforms that are catching up fast. My firm does Salesforce to HubSpot migrations as part of our services, and it's getting easier and easier to switch. Still takes time to retrain and shift business processes to a different philosophy, but we almost always see better usage of the platform, better data, and happier users.
HubSpot is not a replacement for hugely complex organizations that needs to dump tens of millions or more into a Salesforce instance (software + labor), but for mid-size and below it's great.
But, we decidedly don't want to become like Salesforce when we grow up. We have been committed to SMBs for 16+ years now, and not planning to change that anytime soon.
They have grown through a lot of M&A, we built our platform from the ground-up for SMBs.
There is room in the market for both Salesforce and HubSpot to succeed. Salesforce for large enterprises (the Fortune 1000) and HubSpot for SMBs.
I just left Salesforce a bit ago for HubSpot (see my other comment in this thread), and as someone with a bit of a "kool-aid allergy", so to speak, I've been pleasantly surprised by HubSpot's willingness to say "this is what we're good at, and we're going to stick to being really good at that", even when the alternative is potentially really lucrative (but massive pain).
There are a number of ways that life at HubSpot has been a huge improvement to me, but chief among them is that the _employees_ still matter more than the raw "maximum possible profit, screw everything else" focus that I constantly saw at Salesforce, and the "we don't have to eat every single market (poorly) just because others have tried to do so (poorly)" mentality is evidence of that, IMO.
Please keep being that!
And to the grand-parent commenter, I'm _very_ leery of anything that sounds unpleasantly familiar, and probably overly-cynical about large tech companies at this point...and so far I've found pleasant surprises at HubSpot, and I don't see desire (at least yet — it's been only 6 months for me) to be like Salesforce.
I forget where I am sometimes! Of course you're on here. Good job on the product - at my last place the sales people were very keen on it, and kept it extremely up to date. At some point IT forced them to transition to Dynamics, and they were not happy :)
We have a simple chat window that only shows on exit on specific pages of our website (consulting firm). It's been a really efficient way to potential clients to start conversations with us and for us to get them quick and helpful answers. Saves both parties a lot of time and helps both qualify/disqualify each other a lot faster.
There was an entire data set released that had all the medical device injuries and malfunctions listed. Pretty interesting to dive into considering it wasn't previously public.
As a Type 1 diabetic, insulin pumps are a game changer for the entire population that needs to use them. But I think it's understated the risks that come with the devices. In my opinion the benefits outweigh the risks but that is still something you should be able to determine on your own as a user.
Side note: One of the things I see a lot of diabetics miss with insulin pumps is how changes in altitude and air pressure can cause unintended delivery of insulin if you have air bubbles in the cartridge. For those who travel with insulin pumps, make sure to disconnect during changes in altitude (take-off and landing).
If EVs became the primary automobile of drivers, and also became the primary semi-truck form on the road, the economics change significantly. When there's demand for charging from an additional tens of millions or hundreds of millions of vehicles in the US alone, my guess is that prices for electricity are going to increase significantly. Especially prices for any type of fast-charging capability while on the road.
Curious to see what this means in 10-20 years when comparing costs between EVs and ICEs.
That being said, long-term maintenance costs, reduction in road noise, etc. are all a win for EVs.
I don't think it'll play out this way. There's no new tech needed to scale up recharge stations, and they can continue to scale up linearly with demand, so you'd expect the supply will increase to meet demand. Fast-charging stations are most needed near highways where land value isn't too expensive so I think you'll see a lot of solar local to the recharge stations too.
The cost increase in electricity is not due to land, it's due to actually needing to buy the electricity from the grid. Sure you can use solar and storage for each charging site, but then you transform the problem into a land one. Otherwise you need to modernize the grid to support vast numbers of charging stations because solar and storage won't be able to charge enough vehicles.
I agree that the supply will increase long term, but power generation capacity tends to have a fair construction lead time and I would not be surprised if it lags demand as EVs scale out.
Most of the extra energy usage will come from cars charging at night when the demand is low. So there is no need to build new power stations, it will be sufficient to run the existing ones at full capacity at night.
True, but that also heavily incentivizes getting solar where possible, as using that free energy to also power your car makes the investment pay off quite a bit quicker, after which you'll be enjoying almost free energy for most of your needs.
I've been working with Tableau for around 10 years and the most noticeable thing was making it easier for both developers and end-users to use the platform. Everything from mobile, to toolbar improvements, alerts, the API, etc. seem to have really come together.
Now, these could all have very well been in development before the acquisition, but as a whole, the capabilities have grown tremendously since that time.
Also, it seems like the licensing options for smaller businesses has really been focused on since the acquisition. It's become much more affordable for a small business to get and use Tableau compared to 4-5 years ago.
We're looking to bring on a contractor for several projects that need assistance with data engineering and data architecture. You'll be working on GCP and AWS, and the architecture components will be determined by you and the team depending on the needs of the client.
Feel free to send an application to dan @ company name. Would be happy to share more about the specific projects, how we work, etc.