#What is Embedded Software?

[dhirajmarketresearch]

[dawdlecentric]

好きだから -- ぼ虹の日 edit

This is very self indulgent and I wasn't even expecting to finish it in time for boniji day. Maybe I just love the pairing so much I wanna make something for it also cuz I still haven't drawn anything about them lately cuz depression go brrrrr

This is initially from Nijika's POV towards Bocchi but some lyrics strayed from that especially the dog part and the last one. But this could also be from Bocchi's POV visualizing Nijika's feelings about her since the edit did start and end with Bocchi in it so...yeah that's how this edit is interpreted (also I kinda got stuck of not knowing what clips that could fit in some parts so ignore if most of the clips are from episode 8)

Btw at the 「またね」 and 「また明日」 part, I was originally going to put the same lines by both Nijika & Bocchi from the show but it sounds out of place so I scrapped it. Tho if I'm better at editing I could make it work and blend it along with the song without it sounding weird (but I'm not :P)

Another thing is that although the lyrics did say 授業 (class) / 放課後部 (after-school club) / LINE in some parts, I changed it to バイト (part time job or in this case I chose work) / 帰宅部 (go-home club) / LOINE to fit the terms in BTR

[el-ffej]

IMO: Absolutely, positively spot-on. Been a software engineer from 1980 to 2016, and this just nails the tech industry economics (and phases) that I saw then, and that I see now.

Must-read. Brilliantly written and on target. Kudos and applause, OP.

If anyone wants to know why every tech company in the world right now is clamoring for AI like drowned rats scrabbling to board a ship, I decided to make a post to explain what's happening.

(Disclaimer to start: I'm a software engineer who's been employed full time since 2018. I am not a historian nor an overconfident Youtube essayist, so this post is my working knowledge of what I see around me and the logical bridges between pieces.)

Okay anyway. The explanation starts further back than what's going on now. I'm gonna start with the year 2000. The Dot Com Bubble just spectacularly burst. The model of "we get the users first, we learn how to profit off them later" went out in a no-money-having bang (remember this, it will be relevant later). A lot of money was lost. A lot of people ended up out of a job. A lot of startup companies went under. Investors left with a sour taste in their mouth and, in general, investment in the internet stayed pretty cooled for that decade. This was, in my opinion, very good for the internet as it was an era not suffocating under the grip of mega-corporation oligarchs and was, instead, filled with Club Penguin and I Can Haz Cheezburger websites.

Then around the 2010-2012 years, a few things happened. Interest rates got low, and then lower. Facebook got huge. The iPhone took off. And suddenly there was a huge new potential market of internet users and phone-havers, and the cheap money was available to start backing new tech startup companies trying to hop on this opportunity. Companies like Uber, Netflix, and Amazon either started in this time, or hit their ramp-up in these years by shifting focus to the internet and apps.

Now, every start-up tech company dreaming of being the next big thing has one thing in common: they need to start off by getting themselves massively in debt. Because before you can turn a profit you need to first spend money on employees and spend money on equipment and spend money on data centers and spend money on advertising and spend money on scale and and and

But also, everyone wants to be on the ship for The Next Big Thing that takes off to the moon.

So there is a mutual interest between new tech companies, and venture capitalists who are willing to invest $$$ into said new tech companies. Because if the venture capitalists can identify a prize pig and get in early, that money could come back to them 100-fold or 1,000-fold. In fact it hardly matters if they invest in 10 or 20 total bust projects along the way to find that unicorn.

But also, becoming profitable takes time. And that might mean being in debt for a long long time before that rocket ship takes off to make everyone onboard a gazzilionaire.

But luckily, for tech startup bros and venture capitalists, being in debt in the 2010's was cheap, and it only got cheaper between 2010 and 2020. If people could secure loans for ~3% or 4% annual interest, well then a $100,000 loan only really costs $3,000 of interest a year to keep afloat. And if inflation is higher than that or at least similar, you're still beating the system.

So from 2010 through early 2022, times were good for tech companies. Startups could take off with massive growth, showing massive potential for something, and venture capitalists would throw infinite money at them in the hopes of pegging just one winner who will take off. And supporting the struggling investments or the long-haulers remained pretty cheap to keep funding.

You hear constantly about "Such and such app has 10-bazillion users gained over the last 10 years and has never once been profitable", yet the thing keeps chugging along because the investors backing it aren't stressed about the immediate future, and are still banking on that "eventually" when it learns how to really monetize its users and turn that profit.

The pandemic in 2020 took a magnifying-glass-in-the-sun effect to this, as EVERYTHING was forcibly turned online which pumped a ton of money and workers into tech investment. Simultaneously, money got really REALLY cheap, bottoming out with historic lows for interest rates.

Then the tide changed with the massive inflation that struck late 2021. Because this all-gas no-brakes state of things was also contributing to off-the-rails inflation (along with your standard-fare greedflation and price gouging, given the extremely convenient excuses of pandemic hardships and supply chain issues). The federal reserve whipped out interest rate hikes to try to curb this huge inflation, which is like a fire extinguisher dousing and suffocating your really-cool, actively-on-fire party where everyone else is burning but you're in the pool. And then they did this more, and then more. And the financial climate followed suit. And suddenly money was not cheap anymore, and new loans became expensive, because loans that used to compound at 2% a year are now compounding at 7 or 8% which, in the language of compounding, is a HUGE difference. A $100,000 loan at a 2% interest rate, if not repaid a single cent in 10 years, accrues to $121,899. A $100,000 loan at an 8% interest rate, if not repaid a single cent in 10 years, more than doubles to $215,892.

Now it is scary and risky to throw money at "could eventually be profitable" tech companies. Now investors are watching companies burn through their current funding and, when the companies come back asking for more, investors are tightening their coin purses instead. The bill is coming due. The free money is drying up and companies are under compounding pressure to produce a profit for their waiting investors who are now done waiting.

You get enshittification. You get quality going down and price going up. You get "now that you're a captive audience here, we're forcing ads or we're forcing subscriptions on you." Don't get me wrong, the plan was ALWAYS to monetize the users. It's just that it's come earlier than expected, with way more feet-to-the-fire than these companies were expecting. ESPECIALLY with Wall Street as the other factor in funding (public) companies, where Wall Street exhibits roughly the same temperament as a baby screaming crying upset that it's soiled its own diaper (maybe that's too mean a comparison to babies), and now companies are being put through the wringer for anything LESS than infinite growth that Wall Street demands of them.

Internal to the tech industry, you get MASSIVE wide-spread layoffs. You get an industry that used to be easy to land multiple job offers shriveling up and leaving recent graduates in a desperately awful situation where no company is hiring and the market is flooded with laid-off workers trying to get back on their feet.

Because those coin-purse-clutching investors DO love virtue-signaling efforts from companies that say "See! We're not being frivolous with your money! We only spend on the essentials." And this is true even for MASSIVE, PROFITABLE companies, because those companies' value is based on the Rich Person Feeling Graph (their stock) rather than the literal profit money. A company making a genuine gazillion dollars a year still tears through layoffs and freezes hiring and removes the free batteries from the printer room (totally not speaking from experience, surely) because the investors LOVE when you cut costs and take away employee perks. The "beer on tap, ping pong table in the common area" era of tech is drying up. And we're still unionless.

Never mind that last part.

And then in early 2023, AI (more specifically, Chat-GPT which is OpenAI's Large Language Model creation) tears its way into the tech scene with a meteor's amount of momentum. Here's Microsoft's prize pig, which it invested heavily in and is galivanting around the pig-show with, to the desperate jealousy and rapture of every other tech company and investor wishing it had that pig. And for the first time since the interest rate hikes, investors have dollar signs in their eyes, both venture capital and Wall Street alike. They're willing to restart the hose of money (even with the new risk) because this feels big enough for them to take the risk.

Now all these companies, who were in varying stages of sweating as their bill came due, or wringing their hands as their stock prices tanked, see a single glorious gold-plated rocket up out of here, the likes of which haven't been seen since the free money days. It's their ticket to buy time, and buy investors, and say "see THIS is what will wring money forth, finally, we promise, just let us show you."

To be clear, AI is NOT profitable yet. It's a money-sink. Perhaps a money-black-hole. But everyone in the space is so wowed by it that there is a wide-spread and powerful conviction that it will become profitable and earn its keep. (Let's be real, half of that profit "potential" is the promise of automating away jobs of pesky employees who peskily cost money.) It's a tech-space industrial revolution that will automate away skilled jobs, and getting in on the ground floor is the absolute best thing you can do to get your pie slice's worth.

It's the thing that will win investors back. It's the thing that will get the investment money coming in again (or, get it second-hand if the company can be the PROVIDER of something needed for AI, which other companies with venture-back will pay handsomely for). It's the thing companies are terrified of missing out on, lest it leave them utterly irrelevant in a future where not having AI-integration is like not having a mobile phone app for your company or not having a website.

So I guess to reiterate on my earlier point:

Drowned rats. Swimming to the one ship in sight.

[jeeo2cllan]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--32-bit/stm32f429zit6tr-stmicroelectronics-8101935

32 bit embedded microcontrollers software, low power microcontrollers

STM32F Series 2 MB Flash 256 KB RAM 100 MHz 32-Bit Microcontroller - LQFP-144

[dgls2nett]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--8-bit/pic18f4520-i-pt-microchip-3154588

low power 8 bit microcontrollers, lcd microcontrollers, Microcontroller software

PIC18F Series 32 KB Flash 1.5 kB RAM 40 MHz 8-Bit Microcontroller - TQFP-44

[swhn2ltmn]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--32-bit/stm32l471vgt6tr-stmicroelectronics-9173291

What is a microcontroller, lcd microcontrollers, programming microcontroller

STM32L Series 1 MB Flash 128 kB RAM 80 MHz 32-Bit Microcontroller - LQFP-100

[mich2lleyy]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--16-bit-general-purpose/mchc912b32cfue8-nxp-3822756

Microprocessor development board, 16 bit special embedded microcontroller

MCHC91B Series 1 kB RAM 32 kB Flash 16-Bit SMT Flash Microcontroller - QFP-80

[dvdid2ddan]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--32-bit/cy8c5868axi-lp035-infineon-3028673

Microcontroller controller, types of microcontrollers, wireless microcontroller

CY8C5xx Series 256 kB Flash 64 kB RAM 67 MHz SMT 32-Bit PSoC®5 - TQFP-100

[rnk2tmoss]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--32-bit/stm32f437vgt6tr-stmicroelectronics-3169940

Software microcontroller, lcd microcontroller, 32 bit embedded microcontrollers

Arm Cortex-M4 core with DSP and FPU, 1 Mbyte of Flash memory, 180 MHz

[jsph2cobb]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--32-bit/stm32f407zgt6-stmicroelectronics-1016405

32 bit embedded microcontrollers, Pic microcontrollers, USB microcontrollers

STM32F Series 1024 kB Flash 192 kB RAM 168 MHz 32-Bit Microcontroller - LQFP-144

[dhirajmarketresearch]

[shrm2lph]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--8-bit/atmega128l-8au-microchip-2038197

lcd microcontrollers, Low power microcontroller, microcontroller software

ATmega Series 128 KB Flash 4 KB SRAM 8 MHz 8-Bit Microcontroller - TQFP-64

[wliw2ckay]

https://www.futureelectronics.com/p/semiconductors--analog--amplifiers--general-purpose/ts391iylt-stmicroelectronics-5071806

Amplifiers, 16 bit microcontroller, lcd microcontrollers, wireless microcontroller

TS391 Series 36 V 400 nA SMT Single General Purpose Comparator - SOT-23

[ryy2gton]

https://www.futureelectronics.com/p/semiconductors--microcontrollers--8-bit/pic18f6520-i-pt-microchip-7337520

8-bit microprocessor, 8 bit embedded microcontroller, Low power microcontroller

PIC18F Series 32 kB Flash 2 kB RAM 40 MHz 8-Bit Microcontroller - TQFP-64

[infoveave]

Unleashing the Power of Data: The Advantages of Embedded Analytics Software

In today's data-driven world, businesses are constantly seeking ways to extract meaningful insights from the vast amounts of data they generate and collect. Embedded analytics software is emerging as a powerful tool to help companies achieve this goal. By integrating analytics directly into their existing applications and workflows, organizations can unlock valuable insights and drive better decision-making processes.

What is Embedded Analytics Software?

Embedded analytics software is a technology that integrates data analysis and visualization capabilities directly into a business application or process. This integration allows users to access and analyze data within the context of their workflow, without the need to switch to a separate analytics tool or platform.

Key Features and Benefits

One of the key features of embedded analytics software is its ability to provide real-time data insights. By accessing up-to-date information directly within their applications, users can make more informed decisions quickly. This real-time functionality is especially valuable in fast-paced industries where timely decisions can make a significant impact.

Another important benefit of embedded analytics software is its ability to enhance user engagement. By presenting data in a visually appealing and interactive manner, users are more likely to explore and analyze the information, leading to a deeper understanding of key trends and patterns.

Additionally, embedded analytics software can help businesses improve their operational efficiency. By streamlining the data analysis process and eliminating the need for manual data manipulation, organizations can save time and resources, allowing them to focus on other strategic initiatives.

Use Cases

Embedded analytics software can be applied across various industries and use cases. For example, in the retail sector, businesses can use embedded analytics to analyze customer purchasing behavior and optimize their product offerings. By understanding customer preferences and trends, retailers can tailor their marketing strategies to drive sales and increase customer satisfaction.

In the healthcare industry, embedded analytics software can be used to analyze patient data and improve healthcare outcomes. Healthcare providers can use embedded analytics to track patient progress, identify potential health risks, and personalize treatment plans.

Challenges and Considerations

While embedded analytics software offers many benefits, there are also challenges and considerations to keep in mind. One challenge is ensuring the security and privacy of data. Businesses must implement robust security measures to protect sensitive information and comply with data protection regulations.

Another consideration is the integration of embedded analytics into existing systems. Businesses need to ensure that the software is compatible with their current infrastructure and can seamlessly integrate with their applications and workflows.

Conclusion

Embedded analytics software is revolutionizing the way businesses analyze and utilize data. By integrating analytics directly into their applications, organizations can unlock valuable insights, improve decision-making processes, and drive better business outcomes. As the demand for data-driven insights continues to grow, embedded analytics software will play an increasingly important role in helping businesses stay competitive in today's digital landscape.

Original Source: Embedded Analytics Tool

[blockverse-infotech]

Navigating Through the Depths of Embedded Software: Testing and Verification Strategies

In the complex realm of technology, Embedded Systems serve as the quiet foundation, driving a variety of devices from intelligent gadgets to automotive systems. At the core of these systems lies the embedded software, the unseen power coordinating smooth operation. However, ensuring the dependability and strength of this software is not a simple task. Step into the domain of Embedded Systems Testing and Verification, where BlockVerse Infotech Solutions emerges as a beacon of expertise and ingenuity.

In a time where flawless performance is a must, the importance of thorough testing and verification strategies cannot be overstressed. BlockVerse Infotech Solutions acknowledges this necessity and offers a comprehensive method tailored to tackle the distinctive challenges presented by embedded software.

Initially, understanding the complexities of the embedded environment holds great importance. BlockVerse utilizes a combination of white-box and black-box testing methods to explore deep within the software’s internal operations while replicating real-world situations. This detailed approach ensures not only functional accuracy but also deals with performance, reliability, and security concerns.

Moreover, Blockverse utilizes cutting-edge tools and techniques to simplify the testing process. From automated test frameworks to model-based testing, each tool is utilized with precision to optimize efficiency without compromising quality. By utilizing virtual platforms and emulation, BlockVerse enables thorough testing across various hardware configurations, preventing compatibility issues proactively.

However, testing alone does not guarantee the integrity of embedded software. Verification, the process of confirming that the software meets predefined requirements, is equally crucial. BlockVerse adopts a varied verification approach covering code reviews, static analysis, and formal methods. By scrutinizing every line of code and adhering to industry standards, BlockVerse guarantees compliance with strict quality benchmarks.

To wrap up, embedded software plays a crucial role in modern technology, and its reliability is crucial. With BlockVerse Infotech Solutions leading the way, navigating the intricacies of Embedded Systems Testing and Verification becomes more than just a challenge; it transforms into an opportunity to enhance performance, improve reliability, and propel innovation forward.