#software development amortization

[ifindtaxpro]

🔍 IRS issued updated guidelines on Research and experimental Expenses (Code Sec. 174)! Understand the capitalization & amortization rules for R&E costs. Stay compliant & navigate software development expenses effectively. 💡💼 #ResearchExpenses #IRS #Compliance

[mitigatedchaos]

General Post for Monday, April 8, 2024

(~1,600 words, 8 mins)

1 - Robot Jobpocalypse Notes: A brief theory that long-term redistribution to manage job losses from automation should consider focusing on inherently more scarce factors of production (land and materials), rather than more dynamic ones (labor and capital).

2 - Niche Smartphone Notes: If the pace of the smartphone industry were slower, niche smartphones might be more feasible.

3 - Coalitional Politics Notes: Many coalition-internal communications take place in public. Possible implications for loyalty vs. truthfulness.

4 - Lab Leak Notes: Separating the "strong" from "weak" lab leak hypothesis for Covid-19.

5 - Property Notes: Not all labor is equally effortful or valuable, so should claims on property be weighted? Entropy implies the gradual degradation of land and products to a "natural condition," which we might expect to either invalidate or weaken a property claim.

-☆☆☆-

1: Robot Jobpocalypse Notes

I've said this before, but I just want to reiterate:

Everyone already knows about the problem where automation can take over a job faster than the economy finds new jobs for those currently employed in that category. (Obviously we could talk about abstract skill capital that they've invested in the job that has now been made less valuable.)

But over the long term, the thing to think about is a bidding up of the prices of land, materials, and energy. For the first two, we can think of this in terms of rents (e.g. "land rents"), as the supply of land is highly inelastic. In theory, the gains from trade should make everyone better off, but that's only if you can bid high enough to get enough resources to survive. If people could always go back to subsistence farming if they had to, the trade would (almost) always make them better off than subsistence farming.

But without land, they can't. It's not just a matter of not selling, as land is taxed, and higher-value uses will bid up the price of the land, and thus the assessed tax.

We want a redistribution that's dynamic and which will respond to changes in market conditions, which won't dampen investment in capital and production, and which is less subject to political capture. Thus the thing to focus on is rent for land and materials, the inherently scarce factors of production, rather than labor (highly responsive to effort) or capital (material configurations).

2: Niche Smartphone Notes

[ @jadagul ]

They're currently putting out a 4.7" rugged phone, which is actually tempting. But if I wanted a keyboard phone from them, the most recent option is the Titan Slim, which came out in 2021 and runs Android 11. (My current phone is on Android 14.)

[...]

They can make some niche phones, but they just can't cover all the niches. There are too many! And because they're a niche producer, they also have lower quality across a variety of metrics: they can't put as many resources into their software stuff because they can't amortize it across nearly as many phones. In order to get the full advantages of a modern industrial toolchain, you need to standardize some stuff so you can spread development work across a ton of devices.

It's interesting to note that the extremely rapid rate of software development, including finding and patching security flaws, is such an obstacle.

In an Elfworld scenario, where some users are buying a phone for 15-25 year use, firms might be able to amortize the costs by updating the model less frequently, and charging more for the base model. They would likely also maintain smaller teams, who would work on the phones for longer.

Smartphones probably won't become such a stable technology for decades, however, and even if they did, we should expect fashion cycles.

3: Coalitional Politics Notes

We've all seen politicians, political operatives, and political party enthusiasts lie a lot. Why don't they lie to (or bullshit (as in speak as though 'indifferent to truth')) outsiders all the time?

There are a number of reasons. One may be that an insider who constantly lies to outsiders all the time could also lie to fellow insiders, and insiders cannot reliably tell whether someone is a general liar or merely a partisan liar.

Since people range in their level of partisanship, this suggests a curve where, from the perspective of someone who is moderately partisan, a speaker can trade some integrity for some partisan loyalty, and vice versa. Someone who has no loyalty and no integrity is of little value. At some point, partisan loyalty will be at odds with the truth due to the inherent contradiction in interests of the coalition members or else just simple imperfection, so someone cannot be both perfectly loyal and perfectly truthful.

For political coalitions, a lot of what is essentially coalition-internal communication takes place in public.

4: Lab Leak Notes

The debate over the potential lab leak origin of Covid-19 has not been settled yet, despite the article on ACX. People are arguing over the individual studies cited in responses to themotte's tracingwoodgrains.

However, we should differentiate between the "strong" lab leak hypothesis and the "weak" lab leak hypothesis.

Strong Hypothesis: Covid-19 was a bioweapon deliberately designed by the government of China and leaked on purpose for some strategic goal.

Weak Hypothesis: Covid-19 was a coronavirus being studied at the lab in Wuhan which studies coronaviruses. This virus may have been the subject of gain-of-function research not intended to create a bioweapon. Subsequently, as the result of an unintentional accident, the virus leaked from the lab, resulting in a global pandemic.

The criticism of the lab leak hypothesis from the more censorious 2020 libs was that, "The lab leak hypothesis is a racist conspiracy theory." The strong hypothesis is a conspiracy theory, but there is no requirement that it is racist - it is sufficient that the government of China openly identify as Communist. The weak hypothesis is neither of these things.

5: Property Notes

There is an Anarcho-Capitalist theory that ownership of unclaimed land is gained by "mixing your labor with it." Many people would ask why this creates a morally-valid indefinite ownership claim.

Alternatively, we could consider a functional decomposition of the operation.

"Mixing your labor" with the land means using [ attention ] to direct [ energy ] to configure [ matter ] according to your intentions. That might mean, for instance, cutting down trees on a lot in order to construct a fence, and then plowing the lot in order to plant a farm for later harvest. However...

Some people may have the intention for the lot, "It should be a wildlife preserve," which looks an awful lot like doing nothing, or perhaps just posting some signs.

Not all labor is of equal intensity. Should someone who uses less labor, or transforms the lot less, have a proportionally lower % claim on the lot? What does a % claim look like as compared to a full claim?

The configuration on the lot will degrade actively with time if it is not maintained. In our example, the wooden fence may break down and rot. Does this degrade the claim on the lot itself?

The metadata about the lot will also be lost, until it may not be feasible to resolve disputing claims of ownership with reasonable certainty.

Back in January, I wrote:

(Side note: The configuration of material inputs, like ore deposits, in the environment, relates to the amount of energy and attention required to recover them. Recycling is mostly about reducing the long-term recovery costs, keeping materials “near the surface.”)

Let's consider an example.

Joe mines a bunch of iron ore beneath a plot of land. The energy and attention required for most desired human uses is reduced.

Joe refines the iron into steel. The energy and attention required for most desired human uses is again reduced. (Did you know 93% of structural steel is recycled?)

Joe shapes the steel into a grill. This reduces the value of the material for other industrial uses, but increases the value for those who want a grill specifically. The steel is now configured as capital equipment.

Joe opens a hamburger shop, and uses the grill to grill hamburgers which he sells to customers.

After deciding to close the hamburger shop, Joe decides to explode the grill for a gender reveal party, scattering pieces all over the lot. The steel has been scattered throughout the environment, increasing the cost in energy and attention to gather it again if someone wants to do something else with it.

The value of the iron is subjective. That's conventional economics. However, there are typical uses that we can say will be common in most near-term human preference environments.

What makes this interesting is that within that common frame, in steps #1 and #2, Joe is pushing the iron up a value gradient. This value addition could then be lost to entropy through abandonment. For instance, in step #1, a landslide could occur, covering the iron back up and requiring it to be mined again. In step #2, the steel could be left out in the rain to rust, requiring it to be refined again.

Preventing this loss to entropy requires active attention and energy. (For instance, securing a nearby hillside to prevent the landslide scenario, or building and maintaining a barn to keep out the rain in the weathering scenario.)

Suppose that Joe abandons the land for 100 years. The steel rusts, and a landslide covers it up. A new prospector, Harold, comes across the land, finds no markings, excavates the rusted iron, refines it to make tools and sells those tools.

Shortly thereafter, Joe returns. Given that the land and materials returned to the natural condition, wouldn't it be strange to invalidate Harold's claim in this scenario?

Supporting a governing system, which could track ownership of the parcel of land and extracted materials, would require ongoing energy and attention on Joe's part. However, the system of deeds and records could be used as an alternative to Joe physically hanging out on the plot of land at all times, which he would have to do anyway to prevent the reversion of the plot of land to the natural condition.

This movement of materials along value and energy gradients is something to consider for a deeper analysis, perhaps oriented towards the development of new ideological principles.

[mentalisttraceur-software]

histdir

So I've started a stupid-simple shell/REPL history mechanism that's more friendly to Syncthing-style cloud sync than a history file (like basically every shell and REPL do now) or a SQLite database (which is probably appropriate, and it's what Atuin does while almost single-handedly dragging CLI history UX into the 21st century):

You have a history directory.

Every history entry gets its own file.

The file name of a history entry is a hash of that history entry.

The contents of a history entry file is the history entry itself.

So that's the simple core concept around which I'm building the rest. If you just want a searchable, syncable record of everything you ever executed, well there you go. This was the smallest MVP, and I implemented that last night - a little shell script to actually create the histdir entries (entry either passed as an argument or read on stdin if there's no entry argument), and some Elisp code in my Emacs to replace Eshell's built-in history file save and load. Naturally my loaded history stopped remembering order of commands reliably, as expected, which would've been a deal-breaker problem in the long term. But the fact that it instantly plugged into Syncthing with no issues was downright blissful.

(I hate to throw shade on Atuin... Atuin is the best project in the space, I recommend checking it out, and it significantly inspired the featureset and UX of my current setup. But it's important for understanding the design choices of histdir: Atuin has multiple issues related to syncing - histdir will never have any sync issues. And that's part of what made it so blissful. I added the folder to Syncthing - no separate account, no separate keys, nothing I must never lose. In most ways, Atuin's design choice of a SQLite database is just better. That's real, proper engineering. Serious software developers all know that this is exactly the kind of thing where a database is better than a bunch of files. But one benefit you get from this file-oriented granularity is that if you just design the naming scheme right, history entries never collide/conflict in the same file. So we get robust sync, even with concurrent use, on multiple devices - basically for free, or at least amortized with the setup effort for whatever solution you're using to sync your other files (none of which could handle updates from two different devices to a single SQLite database). Deleting a history entry in histdir is an "rm"/"unlink" - in Atuin it's a whole clever engineering puzzle.)

So onto preserving order. In principle, the modification time of these files is enough for ordering: the OS already records when they were last written to, so if you sort on that, you preserve history order. I was initially going to go with this, but: it's moderately inconvenient in some programming languages, it can only handle a 1-to-1 mapping (one last-modified timestamp) even though many uses of history might prefer an n-to-1 (an entry for every time the command was called), and it requires worrying about questions like "does {sync,copy,restore-from-backup,this-programmatic-manipulation-I-quickly-scripted} preserve the timestamp correctly?"

So tonight I did what any self-respecting drank-too-much-UNIX-philosophy-coolaid developer would do: more files. In particular:

Each call of a history entry gets its own file.

The file name of a call is a timestamp.

The contents of a call file is the hash of the history entry file.

The hash is mainly serving the purpose of being a deterministic, realistically-will-never-collide-with-another-history-entry (literally other causes of collision like hackers getting into your box and overwriting your memory are certain and inevitable by comparison) identifier - in a proper database, this would just be the primary key of a table, or some internal pointer.

The timestamp files allow a simple lexical sort, which is a default provided by most languages, most libraries, and built in by default in almost everything that lists/iterates a directory. That's what I do in my latest Elisp code in my Emacs: directory-files does a lexical sort by default - it's not pretty from an algorithmic efficiency standpoint, but it makes the simplest implementation super simple. Of course, you could get reasonably more efficient if you really wanted to.

I went with the hash as contents, rather than using hardlinks or symlinks, because of programmatic introspection simplicity and portability. I'm not entirely sure if the programmatic introspection benefits are actually worth anything in practice. The biggest portability case against symlinks/hardlinks/etc is Windows (technically can do symlinks, but it's a privileged operation unless you go fiddle with OS settings), Android (can't do hardlinks at all, and symlinks can't exist in shared storage), and if you ever want to have your histdir on something like a USB stick or whatever.

Depending on the size of the hash, given that the typical lengths of history entries might be rather short, it might be better for deduplication and storage to just drop the hash files entirely, and leave only the timestamp files. But it's not necessarily so clear-cut.

Sure, the average shell command is probably shorter by a wide margin than a good hash. The stuff I type into something like a Node or Python REPL will trend a little longer than the shell commands. But now what about, say, URLs? That's also history, it's not even that different conceptually from shell/REPL history, and I haven't yet ruled out it making sense for me to reuse histdir for that.

And moreover, conceptually they achieve different goals. The entry files are things that have been in your history (and that you've decided to keep). They're more of a toolbox or repertoire - when you do a fuzzy search on history to re-run a command, duplicates just get in the way. Meanwhile, call files are a "here's what I did", more of a log than a toolbox.

And obviously this whole histdir thing is very expandable - you could have other files containing metadata. Some metadata might be the kind of thing we'd want to associate with a command run (exit status, error output, relevant state like working directory or environment variables, and so on), but other stuff might make more sense for commands themselves (for example: this command is only useful/valid on [list of hosts], so don't use it in auto-complete and fuzzy search anywhere else).

So... I think it makes sense to have history entries and calls to those entries "normalized" into their own separate files like that. But it might be overkill in practice, and the value might not materialize in practice, so that's more in the TBD I guess.

So that's where I'm at now. A very expandable template, but for now I've just replicated basic shell/REPL history, in an a very high-overhead way. A big win is great history sync almost for free, without a lot of the technical downsides or complexity (and with a little effort to set up inotify/etc watches on a histdir, I can have newly sync'ed entries go directly into my running shells/REPLs... I mean, within Emacs at least, where that kind of across-the-board malleability is accessible with a reasonably low amount of effort). Another big win is that in principle, it should be really easy to build on existing stuff in almost any language to do anything I might want to do. And the biggest win is that I can now compose those other wins with every REPL I use, so long as I can either wrap that REPL a little bit (that's how I'll start, with Emacs' comint mode), or patch the common libraries like readline to do histdir, or just write some code to translate between a traditional history file and my histdir approach.

At every step of the way, I've optimized first and foremost for easiest-to-implement and most-accessible-to-work-with decision. So far I don't regret it, and I think it'll help a lot with iteratively trying different things, and with all sorts of integration and composition that I haven't even thought of yet. But I'll undoubtedly start seeing problems as my histdirs grow - it's just a question of how soon and how bad, and if it'll be tractable to fix without totally abandoning the approach. But it's also possible that we're just at the point where personal computers and phones are powerful enough, and OS and FS optimizations are advanced enough, that the overhead will never be perceptible to me for as long as I live - after all, its history for an interface with a live human.

So... happy so far. It seems promising. Tentatively speaking, I have a better daily-driver shell history UX than I've ever had, because I now have great reliable and fast history sync across my devices, without regressions to my shell history UX (and that's saying something, since I was already very happy with zsh's vi mode, and then I was even more happy with Eshell+Eat+Consult+Evil), but I've only just implemented it and given it basic testing. And I remain very optimistic that I could trivially layer this onto basically any other REPL with minimal effort thanks to Emacs' comint mode.

[softcoresolutions]

Effortlessly Manage Recurring Revenue with NetSuite Cloud ERP

The adoption of subscriptions and recurring revenue models has affected almost every modern business in one way or another. From SaaS platforms, media companies, and professional services, income streams that can be predicted have become the new treasure for financial security. Unfortunately, most legacy systems were never designed to deal with modern billing cycle complexities, usage-based pricing, or automated renewals.

Oracle NetSuite Cloud ERP is positioned to bridge that gap. This sophisticated enterprise resource planning system does not only track transactions but also manages the entire customer lifecycle, actively transforming billing operations from a tactical necessity into a competitive advantage.

1. Flexible Billing for Every Business Model

The good thing about recurring revenue is the convenience that comes along with it. However, that very convenience can be a nightmare in itself without the right tools. Oracle NetSuite Cloud ERP can deal with everything from simple monthly subscriptions to much more complex hybrids that include fixed fees and usage-based components. Take, for example, the case of a software company that needs to bill some customers annually, while other customers are billed quarterly, and there are some who require variable rates based on API calls or storage usage. Traditional accounting systems fail under such strain, but NetSuite excels at it.

2. Subscription Management That Actually Scales:

Managing subscribers can be described as a delicate interplay between insight and precision. NetSuite Cloud ERP handles the proactive revenue optimization of subscriber management, turning reactive firefighting into a streamlined process. The system goes beyond merely accepting payments—it offers a holistic vantage point of all customer relationships. NetSuite flags high-value clients who are in danger of churning before it becomes an issue. It alerts subscription services to offer potential upsells to customers who continuously max out their limits. This level of intelligence for rapid growth businesses is crucial in achieving successful scale rather than drowning in operational complexity.

3. Focus on Royalty and Licensing Management:

Like in the media industry, software development and content platforms also face difficulties managing royalties and licensing fees. The myriads of contracts, their differing terms, payment schedules, and complex profit-sharing formulas create an intricate network of financial responsibilities that is nearly impossible to keep track of manually. Oracle NetSuite Cloud ERP provides a solution for all these headaches. Even more importantly, content creators and partners receive precise payments for their contributions on schedule - improving business relations. If a company’s most precious asset is their intellectual property, there is no suitable alternative to his level of financial clarity.

4. Unified Financials: From Billing to Revenue Recognition:

Ensuring compliance isn’t simple, as miscalculations at this stage can lead to restatements, audits, and loss of investor trust. NetSuite Cloud ERP simplifies compliance at every level by automating deferred revenue, revenue allocation, and amortization schedule management over multiple reporting periods. For publicly traded companies or those looking to go public, convenience matters less than avoiding dire financial threats using compliance regulations that protect investors and regulators.

5. What Makes NetSuite Unique Among Others in the ERP Industry:

Among all enterprise resource planning systems, Oracle NetSuite Cloud ERP sits atop the competition for its inherent grasp of businesses with subscription models. While other systems slap on subscription handling as an afterthought, NetSuite was designed from the ground up to manage the complexities of modern business models. Perhaps most importantly, NetSuite adapts to your business growth, managing everything from a startup's first hundred subscribers to an enterprise with millions of customer relationships. Connecting to an always-changing business world is easier with an ERP system without costly tailoring, and NetSuite stands out among the rest.

In our time, one of the most important changes in business is the shift to recurring revenue models. However, none of this is possible without effort. Oracle NetSuite Cloud ERP Systems will change the situation by automating key processes like billing, customer management, and finances, transforming the concept of recurring revenue into a real competitive advantage. SoftCore Solutions, proudly recognized as one of the best Oracle NetSuite Cloud ERP partners in India, further cements this.

FAQs

1. Can NetSuite handle complex subscription tiers?

Careful management of complex subscription tiers is NetSuite’s strong suit. It fully supports simple and flat-rate subscriptions as well as more hybrid systems with fixed, usage-based, and tiered pricing.

2. Does NetSuite adhere to the revenue recognition standards?

The system inherently complies with ASC 606 and IFRS 15 by automating revenue allocation for different time periods and preserving detailed audit trails for effortless financial reporting and auditing.

3. Where can I search for NetSuite specialists in India?

In addition to Oracle, you can search for local implementation gurus using the network of authorized NetSuite partners in India, as these offer training and ongoing maintenance tailored to your business.

[jcmarchi]

AI’s Trillion-Dollar Problem

New Post has been published on https://thedigitalinsider.com/ais-trillion-dollar-problem/

AI’s Trillion-Dollar Problem

As we enter 2025, the artificial intelligence sector stands at a crucial inflection point. While the industry continues to attract unprecedented levels of investment and attention—especially within the generative AI landscape—several underlying market dynamics suggest we’re heading toward a big shift in the AI landscape in the coming year.

Drawing from my experience leading an AI startup and observing the industry’s rapid evolution, I believe this year will bring about many fundamental changes: from large concept models (LCMs) expected to emerge as serious competitors to large language models (LLMs), the rise of specialized AI hardware, to the Big Tech companies beginning major AI infrastructure build-outs that will finally put them in a position to outcompete startups like OpenAI and Anthropic—and, who knows, maybe even secure their AI monopoly after all.

Unique Challenge of AI Companies: Neither Software nor Hardware

The fundamental issue lies in how AI companies operate in a previously unseen middle ground between traditional software and hardware businesses. Unlike pure software companies that primarily invest in human capital with relatively low operating expenses, or hardware companies that make long-term capital investments with clear paths to returns, AI companies face a unique combination of challenges that make their current funding models precarious.

These companies require massive upfront capital expenditure for GPU clusters and infrastructure, spending $100-200 million annually on computing resources alone. Yet unlike hardware companies, they can’t amortize these investments over extended periods. Instead, they operate on compressed two-year cycles between funding rounds, each time needing to demonstrate exponential growth and cutting-edge performance to justify their next valuation markup.

LLMs Differentiation Problem

Adding to this structural challenge is a concerning trend: the rapid convergence of large language model (LLM) capabilities. Startups, like the unicorn Mistral AI and others, have demonstrated that open-source models can achieve performance comparable to their closed-source counterparts, but the technical differentiation that previously justified sky-high valuations is becoming increasingly difficult to maintain.

In other words, while every new LLM boasts impressive performance based on standard benchmarks, a truly significant shift in the underlying model architecture is not taking place.

Current limitations in this domain stem from three critical areas: data availability, as we’re running out of high-quality training material (as confirmed by Elon Musk recently); curation methods, as they all adopt similar human-feedback approaches pioneered by OpenAI; and computational architecture, as they rely on the same limited pool of specialized GPU hardware.

What’s emerging is a pattern where gains increasingly come from efficiency rather than scale. Companies are focusing on compressing more knowledge into fewer tokens and developing better engineering artifacts, like retrieval systems like graph RAGs (retrieval-augmented generation). Essentially, we’re approaching a natural plateau where throwing more resources at the problem yields diminishing returns.

Due to the unprecedented pace of innovation in the last two years, this convergence of LLM capabilities is happening faster than anyone anticipated, creating a race against time for companies that raised funds.

Based on the latest research trends, the next frontier to address this issue is the emergence of large concept models (LCMs) as a new, ground-breaking architecture competing with LLMs in their core domain, which is natural language understanding (NLP).

Technically speaking, LCMs will possess several advantages, including the potential for better performance with fewer iterations and the ability to achieve similar results with smaller teams. I believe these next-gen LCMs will be developed and commercialized by spin-off teams, the famous ‘ex-big tech’ mavericks founding new startups to spearhead this revolution.

Monetization Timeline Mismatch

The compression of innovation cycles has created another critical issue: the mismatch between time-to-market and sustainable monetization. While we’re seeing unprecedented speed in the verticalization of AI applications – with voice AI agents, for instance, going from concept to revenue-generating products in mere months – this rapid commercialization masks a deeper problem.

Consider this: an AI startup valued at $20 billion today will likely need to generate around $1 billion in annual revenue within 4-5 years to justify going public at a reasonable multiple. This requires not just technological excellence but a dramatic transformation of the entire business model, from R&D-focused to sales-driven, all while maintaining the pace of innovation and managing enormous infrastructure costs.

In that sense, the new LCM-focused startups that will emerge in 2025 will be in better positions to raise funding, with lower initial valuations making them more attractive funding targets for investors.

Hardware Shortage and Emerging Alternatives

Let’s take a closer look specifically at infrastructure. Today, every new GPU cluster is purchased even before it’s built by the big players, forcing smaller players to either commit to long-term contracts with cloud providers or risk being shut out of the market entirely.

But here’s what is really interesting: while everyone is fighting over GPUs, there has been a fascinating shift in the hardware landscape that is still largely being overlooked. The current GPU architecture, called GPGPU (General Purpose GPU), is incredibly inefficient for what most companies actually need in production. It’s like using a supercomputer to run a calculator app.

This is why I believe specialized AI hardware is going to be the next big shift in our industry. Companies, like Groq and Cerebras, are building inference-specific hardware that’s 4-5 times cheaper to operate than traditional GPUs. Yes, there’s a higher engineering cost upfront to optimize your models for these platforms, but for companies running large-scale inference workloads, the efficiency gains are clear.

Data Density and the Rise of Smaller, Smarter Models

Moving to the next innovation frontier in AI will likely require not only greater computational power– especially for large models like LCMs – but also richer, more comprehensive datasets.

Interestingly, smaller, more efficient models are starting to challenge larger ones by capitalizing on how densely they are trained on available data. For example, models like Microsoft’s FeeFree or Google’s Gema2B, operate with far fewer parameters—often around 2 to 3 billion—yet achieve performance levels comparable to much larger models with 8 billion parameters.

These smaller models are increasingly competitive because of their high data density, making them robust despite their size. This shift toward compact, yet powerful, models aligns with the strategic advantages companies like Microsoft and Google hold: access to massive, diverse datasets through platforms such as Bing and Google Search.

This dynamic reveals two critical “wars” unfolding in AI development: one over compute power and another over data. While computational resources are essential for pushing boundaries, data density is becoming equally—if not more—critical. Companies with access to vast datasets are uniquely positioned to train smaller models with unparalleled efficiency and robustness, solidifying their dominance in the evolving AI landscape.

Who Will Win the AI War?

In this context, everyone likes to wonder who in the current AI landscape is best positioned to come out winning. Here’s some food for thought.

Major technology companies have been pre-purchasing entire GPU clusters before construction, creating a scarcity environment for smaller players. Oracle’s 100,000+ GPU order and similar moves by Meta and Microsoft exemplify this trend.

Having invested hundreds of billions in AI initiatives, these companies require thousands of specialized AI engineers and researchers. This creates an unprecedented demand for talent that can only be satisfied through strategic acquisitions – likely resulting in many startups being absorbed in the upcoming months.

While  2025 will be spent on large-scale R&D and infrastructure build-outs for such actors, by 2026, they’ll be in a position to strike like never before due to unrivaled resources.

This isn’t to say that smaller AI companies are doomed—far from it. The sector will continue to innovate and create value. Some key innovations in the sector, like LCMs, are likely to be led by smaller, emerging actors in the year to come, alongside Meta, Google/Alphabet, and OpenAI with Anthropic, all of which are working on exciting projects at the moment.

However, we’re likely to see a fundamental restructuring of how AI companies are funded and valued. As venture capital becomes more discriminating, companies will need to demonstrate clear paths to sustainable unit economics – a particular challenge for open-source businesses competing with well-resourced proprietary alternatives.

For open-source AI companies specifically, the path forward may require focusing on specific vertical applications where their transparency and customization capabilities provide clear advantages over proprietary solutions.

[accountingsource]

Valuing Innovation: Accounting for intellectual property in today’s idea-driven economy

Recent decades have brought about a significant shift in the global economy. We’ve moved away from the factories and smokestacks of the past and towards an economy fueled by ideas. Where physical resources and manufacturing prowess were once the primary drivers of economic growth, today, knowledge, creativity, and innovation reign supreme.

Are you looking for Services that can solve your technical accounting challenges? Click here to visit our page!

Innovation has emerged as the cornerstone of economic competitiveness, driving advancements in technology, science, and business practices. At the heart of this transformation is the recognition that intellectual capital, rather than physical assets, holds the key to sustainable growth and prosperity in the modern world.

The modern economy revolves around two key concepts: innovation and intellectual property (“IP”). Innovation fuels progress by continually introducing new products, services, and technologies that respond to consumers’ dynamic needs. Intellectual property provides the essential legal framework to safeguard and incentivize this innovation. Innovation and IP form the bedrock of today’s thriving and dynamic economy.

What’s shaping today’s intellectual property landscape?

The emergence of a knowledge-based economy has reshaped how companies approach IP. With the rise of innovative technologies and the growing emphasis on automation and digitalization, businesses increasingly invest in developing valuable IP assets in-house. This encompasses creating proprietary software solutions tailored to automate processes, catering to the evolving needs of consumers and businesses.

These in-house innovations represent a significant departure from traditional IP acquisition models. The shift poses unique challenges in accounting, particularly in reconciling differences between accounting for acquired IP and internally generated IP.

Intellectual property in the accounting domain

The significant distinction between the accounting treatments for acquired and internally generated intellectual property (IP) lies in their initial recognition and measurement. While acquired IP is generally recognized at cost, internally generated IP is typically expensed unless specific criteria are met. However, once recognized, the subsequent accounting implications for both types of IP are generally similar, including amortization, impairment testing, and disclosure requirements.

Adherence to accounting standards like IAS 38 under the International Financial Reporting Standards (“IFRS”) and ASC 350 under U.S. Generally Accepted Accounting Principles (“US GAAP”) necessitates a thorough understanding of these nuances. This article aims to provide guidance on the proper recognition and initial measurement of internally generated IP, offering insights to appropriately account for their intellectual property assets in today’s era of innovation and knowledge-based economy.

The next section outlines the recognition criteria for internally generated intangibles under IFRS and U.S. GAAP.

Accounting for internally generated IP

Accounting for internally generated software under U.S. GAAP

The accounting treatment for software development costs can differ depending on the software’s intended purpose. This section specifically applies only to US GAAP.

New tax treatment of R&D expenses under the Tax Cuts and Jobs Act

The Tax Cuts and Jobs Act (TCJA) has significantly changed the tax treatment of research and development (R&D) expenses. Prior to the TCJA, businesses could generally deduct these expenses in the year they were incurred. However, for tax years beginning on or after January 1, 2022, the TCJA mandates that these costs, for tax purposes, be capitalized and amortized—spread out over five (5) years for domestic research or fifteen (15) years for international research. This guidance can be found under Section 174 of the Internal Revenue Code.

Another notable change under the TCJA is including software development costs within the definition of R&D expenses. This means software development costs are subject to the same capitalization and amortization requirements. It’s essential to note that this change impacts tax reporting only. The financial statement treatment of R&D expenses remains governed by accounting standards like Generally Accepted Accounting Principles (GAAP). While the tax rules have changed, companies must continue to follow their standard accounting practices for financial reporting purposes.

These changes can significantly impact companies with substantial R&D expenses. Even if a company reports a financial loss on its books, the new rules could still lead to taxable income due to the capitalization of R&D costs, potentially increasing the company’s tax burden.

How Scrubbed can help

The diverse nature of intellectual property today can pose challenges in pinpointing the necessary and appropriate accounting guidance to apply, a task that is both crucial and complex. The Scrubbed Technical Accounting Group can assist you in evaluating specific scenarios related to intellectual property and intangibles (IAS 38 and ASC 350). Whether it’s analyzing complex accounting transactions, crafting comprehensive memos, and ensuring adherence to presentation and disclosure requirements under specific guidance and regulatory mandates, our team is equipped to guide you.

Get in touch with Scrubbed to discover how our Technical Accounting Group can assist your business in navigating accounting complexities associated with intellectual property.

[thealgorithmblog]

How to Build a SaaS Financial Model

Building a SaaS (Software as a Service) financial model involves creating a detailed projection of revenue, expenses, and key performance indicators (KPIs) to help manage growth, profitability, and financial health. Here's a step-by-step guide to building a comprehensive SaaS financial model:

1. Define Key Metrics

Start by identifying the key metrics you'll need to track and project. Common SaaS metrics include:

Monthly Recurring Revenue (MRR): The recurring income generated each month from subscription customers.

Customer Acquisition Cost (CAC): The cost of acquiring a new customer.

Churn Rate: The percentage of customers who cancel their subscriptions each month.

Customer Lifetime Value (LTV): The total revenue expected from a customer over their lifetime.

Average Revenue Per User (ARPU): The average monthly revenue generated per user.

Gross Margin: The revenue remaining after deducting the direct costs associated with delivering the SaaS service.

2. Create Revenue Projections

SaaS companies usually have subscription-based revenue, so your revenue model needs to capture:

Pricing Strategy: Define how much customers will pay and for which subscription tiers (monthly, annual, etc.).

Customer Growth Rate: Estimate the number of new customers added each month (or year).

Churn Rate: Estimate how many customers will leave each month.

Expansion Revenue: Estimate upsells, cross-sells, and price increases.

Example:

If your pricing tiers are $50/month for Basic, $100/month for Standard, and $200/month for Premium, you would estimate the number of customers in each tier over time.

3. Estimate Operating Expenses

SaaS companies incur several types of expenses, including:

Cost of Goods Sold (COGS): These are the direct costs associated with running the service (e.g., hosting, customer support, and maintenance).

Sales and Marketing: Expenses related to acquiring and retaining customers, including advertising, promotions, sales commissions, and salaries.

Research and Development (R&D): Costs of product development and innovation.

General and Administrative (G&A): Costs such as salaries for management, office space, legal fees, and accounting.

You can calculate these based on historical data or industry benchmarks.

4. Develop a Cash Flow Model

Understanding cash flow is critical for SaaS businesses. Since many SaaS businesses have annual subscriptions, the cash flow model should:

Track the inflow of cash from subscription payments (monthly or annual).

Account for how much cash is spent on operating expenses.

Include funding rounds, loans, or any external capital that may affect cash flow.

5. Project Profit and Loss (P&L)

Once you have revenue projections and expense estimates, project your Profit and Loss statement:

Gross Profit: Revenue minus COGS.

EBITDA: Earnings before interest, taxes, depreciation, and amortization. This is a key profitability measure.

Net Profit: Final profit after all expenses, taxes, and interest.

6. Account for Growth and Scaling

SaaS businesses scale quickly, and costs associated with growth need to be considered. Some factors to include are:

Operating Leverage: SaaS companies often have high gross margins that increase as they scale.

Hiring Plans: As you grow, you’ll likely need to hire more staff for sales, support, or product development.

Scaling Infrastructure: Budget for additional servers, data storage, or software integrations.

7. Build Key Performance Indicators (KPIs) Dashboard

Create a dashboard to track your SaaS KPIs over time. Some important KPIs include:

MRR Growth: Monthly growth rate of recurring revenue.

Customer Acquisition Cost (CAC): How much you spend to acquire each customer.

Churn Rate: Customer attrition percentage.

LTV to CAC Ratio: Measures the efficiency of your sales and marketing efforts.

8. Financial Model Template Tools

There are financial model templates available online (Google Sheets, Excel, etc.) that can simplify this process. Some tools to consider:

SaaS Financial Model in Excel/Google Sheets: Templates specifically for SaaS businesses.

SaaS Financial Planning Tools: Tools like ProfitWell, Baremetrics, or LivePlan that offer SaaS-specific metrics and financial projections.

9. Scenario Analysis

To prepare for various business outcomes, build different scenarios (e.g., best case, worst case, and base case) to understand the potential range of financial outcomes.

10. Review and Update Regularly

Financial models are living documents. You should review and adjust your projections regularly, especially as your business grows and market conditions change.

By following these steps, you’ll create a comprehensive financial model that helps you understand your SaaS company’s financial health, plan for future growth, and attract investors or partners.

View More Detailed Article On: How to Build a SaaS Financial Model

[linneajospeh]

Top Tax Strategies for Startups

Starting a new business can be an exciting yet daunting task. While the focus is often on growth and development, managing tax obligations effectively is crucial to ensure long-term success. Implementing smart tax strategies early on can save your startup significant amounts of money and avoid potential issues down the road. Below are some of the top tax strategies for startups to consider:

1. Choose the Right Business Structure

One of the most important decisions you’ll make early in your startup’s life is choosing the right legal structure. The structure you choose—whether it’s a sole proprietorship, LLC, S-corp, or C-corp—will have a direct impact on your tax obligations. For instance, an S-corp allows profits to pass through to shareholders' tax returns, avoiding the double taxation that C-corps face. Consulting with a tax advisor or accountant is essential to ensure the best choice for your business.

2. Take Advantage of Start-Up Expense Deductions

The IRS allows startups to deduct up to $5,000 in qualifying start-up costs in the first year, provided your total startup expenses are under $50,000. These costs can include research, product development, and legal fees. The remaining costs can be amortized over 15 years. These deductions can provide much-needed cash flow relief during the initial stages of your business.

3. Leverage Tax Credits

Startups should explore various tax credits available, such as the Research and Development (R&D) Tax Credit. This credit rewards businesses for developing or improving products and processes, including software development. By claiming this credit, startups can reduce their tax liabilities, potentially recovering a portion of the costs involved in innovation. Additionally, certain green initiatives or employee hiring programs may qualify for other credits, so it’s important to keep up with current incentives.

4. Make the Most of Section 179 Deductions

Section 179 of the IRS tax code allows businesses to immediately deduct the cost of qualifying equipment and software rather than depreciating the cost over time. This deduction can be especially beneficial for startups that need to invest in capital assets like computers, office furniture, and machinery. For the 2024 tax year, businesses can deduct up to $1.16 million, with a phase-out threshold of $2.89 million. This deduction can significantly reduce your startup's taxable income.

5. Contribute to Retirement Plans

Setting up a retirement plan, such as a Solo 401(k) or SEP IRA, is a great way for startup owners and employees to save for retirement while reducing taxable income. Contributions to these plans are tax-deductible, and for a startup, this can help lower the overall tax burden. Additionally, offering retirement benefits can help attract and retain talent, which is critical in the early stages of growth.

6. Keep Detailed Records

Maintaining meticulous records of all business expenses, receipts, and financial transactions is essential for maximizing tax deductions. The IRS scrutinizes businesses with sloppy records, and poor documentation can lead to missed deductions or costly penalties. Use accounting software or hire an accountant for accurate financial tracking and timely filing.

7. Defer Income When Possible

For startups in the early stages of growth, deferring income to the following year can be a smart tax strategy. This is especially useful if you expect to be in a lower tax bracket next year. By deferring income, you can lower your current-year taxable income, resulting in a lower tax liability.

Conclusion

Effective tax planning is essential for startups to build a strong financial foundation. By choosing the right structure, leveraging available deductions and credits, investing in retirement plans, and maintaining detailed records, you can ensure your startup remains financially efficient and poised for growth. Consulting with tax professionals from tax planning for companies in Fort Worth, TX to tailor strategies to your specific situation is always a wise move.

[aeautoevcharger]

AEAUTO: Leading the new trend of electric steering-by-wire for commercial vehicles

At a time when heavy-duty commercial vehicles are undergoing electrification and autonomous driving, innovation in commercial vehicle steering systems is crucial. AEAUTO stands out in the field of commercial vehicle electric steering-by-wire with its superior technology and products.

At present, the development of autonomous driving functions for commercial vehicles has encountered technical difficulties. Foreign products are not sold in China, and the domestic commercial vehicle market has an increasingly strong demand for localization. Traditional and electric hydraulic steering dares to challenge and successfully develop the first generation of commercial vehicle electric wire-controlled steering systems, bringing a new solution to the industry.

Advantages of AEAUTO Electric Steering-by-Wire System

1. System efficiency increased by 30%.

There is no energy loss in the hydraulic link, and the design combines electric and wire control, which perfectly meets the needs of heavy-duty commercial vehicles such as electric vehicles and self-driving heavy trucks.

2. System weight reduced by 35%.

Compared with traditional hydraulic or electric hydraulic steering, this system eliminates five components such as the hydraulic pump and hydraulic steering gear, and steering is completely driven by an electric motor, which is light in weight and small in size.

The total system cost is reduced by 20%. After removing multiple components and amortizing the R&D investment and mold costs, the overall cost of parts is greatly reduced.

AEAUTO electric steering-by-wire system core technology advantages

1. 8000Nm high torque output.

Through a dual-winding motor, high-precision ball screw, and flat secondary enveloping toroidal worm reduction mechanism, as well as a 24V high power density motor and patented reduction mechanism, the 8000Nm high torque output required for heavy-duty commercial vehicles is achieved.

2. High-reliability redundant design.

Using a functional safety-based redundant architecture with dual-winding motors, dual MCUs, and dual control chips for heavy-duty commercial vehicles ensures high reliability and safety of the steering system, meeting the urgent needs of the electric steering system as a functional safety component.

3. The angle control response time does not exceed 50ms.

Based on the in-loop dynamic tracking and feedback control strategy of the power assist value, it adopts a low-inertia permanent magnet synchronous motor, determines the control mode through different sensor signals, and uses the control algorithm to accurately track the target parameters to achieve rapid response of EPS power assist, which is at the international leading level.

Compared with foreign competitors, AEAUTO has better performance in terms of system voltage and angle control response time. Although 48V voltage is designed to output more power, it is not a common standard. AEAUTO also achieves high power output with its unique reduction mechanism without affecting matching and compatibility. In addition, the company's control strategy and algorithm are outstanding, achieving a better angle control response time.

AEAUTO electric steering-by-wire helps heavy-duty trucks become more electrified and autonomous

Our products have undergone a series of rigorous tests, including performance tests, bench tests, and durability tests, and obtained the EU CE certification in June 2021. In terms of customer cases, the electric buses of Karsan in Europe and the products of Otokar, a leading Turkish bus company, both use AEAUTO's electric steer-by-wire system and are sold to many European countries and the United States.

In addition, AEAUTO has also built a heavy-duty commercial vehicle electric steering R&D test platform, which covers software-in-the-loop simulation, testing, calibration, reliability, and durability test benches, and has passed the assessment of Nanjing Engineering Technology Center.

With its advanced technology, excellent product performance, and reliable quality, AEAUTO has demonstrated strong competitiveness in the field of electric steer-by-wire for commercial vehicles and has made positive contributions to promoting the electrification and autonomous driving development of heavy-duty commercial vehicles.

[gallaghermohanusa]

Common Pitfalls in Real Estate Financial Analysis and How to Avoid Them

Real Estate Financial Analysis is vital for making informed decisions in real estate investing and development. However, there are several common pitfalls that can undermine the accuracy and effectiveness of your analysis. Recognizing these mistakes and implementing strategies to avoid them can help ensure a more reliable and successful financial assessment. Here’s a guide to common pitfalls and how to sidestep them.

1. Overlooking Accurate Data Collection

Pitfall: Relying on inaccurate or incomplete data can lead to flawed financial projections and misguided investment decisions. Common issues include outdated market data, incorrect expense estimates, and inaccurate rental income projections.

How to Avoid:

- Verify Data Sources: Use reliable and up-to-date sources for market data and financial information. Cross-check figures with multiple sources when possible.

- Conduct Thorough Research: Ensure comprehensive data collection, including detailed property expenses, local market trends, and comparable property analyses.

- Regular Updates: Continuously update your data to reflect current market conditions and financial status.

2. Ignoring Hidden Costs

Pitfall: Failing to account for all potential costs, such as maintenance, management fees, and unexpected repairs, can lead to underestimating the total investment required and overestimating profitability.

How to Avoid:

- Include All Expenses: Factor in all direct and indirect costs, including property management fees, maintenance, utilities, insurance, property taxes, and vacancy rates.

- Create a Contingency Fund: Set aside a contingency fund for unexpected expenses and emergencies to cover unforeseen costs.

- Review Historical Costs: Analyze historical data from similar properties to estimate potential hidden costs more accurately.

3. Miscalculating Cash Flow

Pitfall: Errors in calculating cash flow can significantly impact financial analysis. Common mistakes include incorrect estimates of rental income or failing to account for debt service and operating expenses.

How to Avoid:

- Detailed Cash Flow Projections: Create detailed cash flow projections that include all sources of income and expenses. Ensure that both operating expenses and financing costs are accurately reflected.

- Regular Monitoring: Continuously monitor cash flow throughout the investment lifecycle to identify and address any discrepancies or issues promptly.

- Use Financial Software: Leverage financial analysis tools and software to improve accuracy and streamline calculations.

4. Overestimating Rental Income

Pitfall: Overestimating potential rental income can lead to unrealistic expectations and financial projections. This often occurs when assuming higher-than-market rental rates or occupancy levels.

How to Avoid:

- Conduct Market Research: Perform thorough market research to determine realistic rental rates and occupancy levels based on comparable properties and current market conditions.

- Use Conservative Estimates: Apply conservative estimates for rental income and occupancy rates to account for potential fluctuations and vacancies.

- Review Lease Agreements: Analyze existing lease agreements and rental history to validate income projections.

5. Underestimating Financing Costs

Pitfall: Misjudging financing costs, such as interest rates, loan fees, and amortization schedules, can lead to inaccurate financial projections and cash flow analysis.

How to Avoid:

- Review Loan Terms: Thoroughly review all loan terms, including interest rates, fees, and repayment schedules. Use these terms in your financial analysis to estimate accurate financing costs.

- Consult Financial Advisors: Work with financial advisors or mortgage brokers to obtain accurate information on financing options and costs.

- Model Different Scenarios: Create financial models with different financing scenarios to understand the impact of various interest rates and loan structures on the project’s financial performance.

6. Neglecting Market Trends

Pitfall: Ignoring market trends and economic conditions can result in unrealistic financial projections and investment decisions. Changes in the local real estate market, interest rates, and economic factors can significantly affect property performance.

How to Avoid:

- Monitor Market Trends: Stay informed about current market trends, including property values, rental rates, and economic conditions. Use this information to adjust your financial projections and investment strategy.

- Perform Sensitivity Analysis: Conduct sensitivity analysis to assess how changes in market conditions, such as interest rates and rental income, impact the financial performance of the property.

- Adapt to Market Changes: Be prepared to adapt your financial analysis and investment strategy based on evolving market conditions and economic factors.

7. Overlooking Tax Implications

Pitfall: Failing to consider tax implications can lead to unexpected liabilities and affect the overall profitability of the investment. This includes overlooking potential deductions, credits, and tax liabilities.

How to Avoid:

- Understand Tax Regulations: Familiarize yourself with relevant tax regulations and how they impact real estate investments, including deductions for depreciation, mortgage interest, and operating expenses.

- Consult Tax Professionals: Work with tax professionals to ensure accurate tax planning and to maximize potential tax benefits.

- Incorporate Tax Implications: Include tax considerations in your financial analysis to better understand the overall impact on profitability.

8. Ignoring Long-Term Sustainability

Pitfall: Focusing solely on short-term financial performance without considering long-term sustainability can lead to overlooking potential future costs and risks.

How to Avoid:

- Evaluate Long-Term Projections: Analyze long-term financial projections, including future maintenance costs, property appreciation, and potential changes in market conditions.

- Plan for Maintenance: Budget for ongoing maintenance and capital improvements to ensure the property remains in good condition and retains its value over time.

- Assess Risk Factors: Identify and plan for long-term risk factors, such as market fluctuations, economic downturns, and changes in regulations.

Conclusion

Avoiding common pitfalls in real estate financial analysis requires attention to detail, thorough research, and careful consideration of all relevant factors. By addressing issues such as inaccurate data, hidden costs, and financing miscalculations, you can enhance the accuracy and reliability of your financial analysis. Implementing these strategies will help you make more informed investment decisions, optimize returns, and achieve long-term success in real estate.

[forblogmostly]

Apollo Micro Systems Limited: Pioneering India's Defense Technology with Unprecedented Growth in Q1 FY25

Apollo Micro Systems Limited (AMS) has always been at the forefront of India's defense technology landscape, a position further solidified by its remarkable performance in the first quarter of FY25. As one of India's leading electronic, electro-mechanical, engineering design, and manufacturing companies, AMS has consistently demonstrated its commitment to innovation, operational excellence, and sustainable growth. Established in 1985, the company has built an impressive legacy, specializing in high-performance solutions that are crucial for mission-critical and time-sensitive operations.

AMS’s product portfolio spans a wide range of industries, including aerospace systems, ground defense, space, avionics systems, homeland security, and transportation. The company's manufacturing facility, located in Hyderabad, spans 55,000 square feet and houses a team of over 300 employees, including more than 150 dedicated to research and development (R&D). This focus on R&D has allowed AMS to remain at the cutting edge of technology, contributing to its role as a key partner in numerous defense programs.

The company’s extensive experience of over 39 years in designing, developing, and assembling custom-built electronics and electro-mechanical solutions is a testament to its expertise. AMS offers a comprehensive range of products and services, from electronic manufacturing services and PCB fabrication to embedded software design and development, circuit board assembly, and hardware design services. Its manufacturing plant is equipped with a full-fledged Environmental Stress Screening (ESS) testing facility, with inspections conducted in line with Defense Quality Assurance (DGQA) standards.

AMS’s reputation is further bolstered by its certifications and approvals, including ISO and CEMILAC certifications and recognition as a Defense Research and Development Organization (DRDO) approved partner. The company plays a key role in multiple ongoing defense programs, with a significant portion of its revenue—between 7-8%—reinvested into R&D. This investment supports the development and testing of critical components under DRDO programs, reinforcing AMS’s position as a leader in defense technology.

The company’s diverse clientele includes prominent government institutions such as the DRDO, the Indian Army, the Indian Navy, and Defense Public Sector Undertakings (DPSUs), as well as private sector giants like Adani and Larsen & Toubro. Some of the key strategic projects undertaken by AMS include the Universal Homing System for Light & Heavy Weight Torpedoes, Landing Gear Actuators for Avionic Platforms, Digital RF Seeker Signal Processor, Integrated Guidance Kit for Various Platforms, and Under Water Mines.

AMS’s capabilities extend across several sectors, including missile systems, aerospace systems, naval systems, satellite space systems, and homeland security. The company’s expertise in on-board electronic weapon systems and ground support equipment for these sectors has made it a trusted partner in the defense industry. AMS also excels in the integration of weapon and platform systems, hardware design, embedded software design and development, and electronic manufacturing services, offering a comprehensive suite of product- and service-based solutions.

The company’s financial performance in Q1 FY25 is a reflection of its robust operational capabilities and strategic vision. AMS reported a significant increase in revenue, achieving Rs. 912.02 million in Q1 FY25, up from Rs. 576.91 million in Q1 FY24. This 58.09% year-on-year growth was primarily driven by robust order execution. The company’s Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA) also saw a substantial rise, reaching Rs. 223.71 million in Q1 FY25, a 75.57% increase from Rs. 127.42 million in Q1 FY24. This growth in EBITDA was fueled by the increased scale of operations, with the EBITDA margin improving to 24.53% in Q1 FY25 from 22.09% in the same quarter of the previous fiscal year.

Profit After Tax (PAT) for Q1 FY25 also saw an impressive increase, reaching Rs. 84.29 million, compared to Rs. 16.54 million in Q1 FY24. The PAT margin improved significantly to 9.24% in Q1 FY25, up from 2.87% in Q1 FY24. These financial achievements underscore AMS’s commitment to operational excellence and sustainable growth, positioning the company for continued success in the future.

AMS’s order book for Q1 FY25 reflects a strong and growing pipeline of projects, underscoring the company’s market leadership and the trust it has earned from its customers. The order book has expanded significantly, driven by high demand across various sectors. The diversity and quality of these orders ensure a stable revenue stream and enhanced profitability, positioning AMS to capitalize on emerging opportunities and maintain its growth momentum.

In a significant milestone, AMS has been shortlisted and awarded a prestigious Make II project by the Indian Army. This project involves the procurement of a Vehicle Mounted Counter Swarm Drone System (VMCSDS) (Version I) under the Make II category of the Defense Acquisition Procedure (DAP) 2020. The award of this project, the company’s first under the Make II category, is a testament to AMS’s capabilities and innovation. The systems developed from this project are state-of-the-art and highly futuristic, reflecting AMS’s commitment to advancing technology and supporting national defense. Importantly, as a Make II project, there will be no cost obligation involved, ensuring efficient and effective execution.

AMS is also investing in its future growth by developing two state-of-the-art modern manufacturing units, cumulatively measuring approximately 400,000 square feet. The development of these facilities is progressing on time and will significantly expand AMS’s scale of operations in the near future.

The Indian government has set an ambitious goal to export over Rs. 50,000 crore worth of defense equipment by the fiscal year 2028-2029. In the 2023-24 financial year, the value of defense production surged to Rs. 1,26,887 crore, marking a significant 16.8 percent increase compared to the previous year. This substantial growth underscores the momentum in the defense sector and reflects the government’s commitment to enhancing India’s position as a global leader in defense manufacturing. To support this vision, the government is dedicated to fostering a more favorable environment for the defense industry, implementing policies and initiatives aimed at strengthening India’s capabilities and competitiveness on the global stage. Through these efforts, India is poised to become a key player in the international defense market, contributing to both national security and economic growth.

Looking ahead, AMS is confident about its future growth prospects. The strong demand for electronic solutions in the defense sector, combined with the company’s highly specialized technology solutions, positions it well to capitalize on opportunities in this space. AMS remains committed to exploring new avenues for innovation, forging strategic partnerships, and striving for operational efficiency in its operations.

The company extends its gratitude to its employees, customers, and shareholders for their unwavering support. As AMS continues to create value, it looks forward to a successful future, driving forward the mission of strengthening defense systems for a self-reliant India.

[reitmonero]

The Ultimate Tax Planning Checklist for Startups

1. Understand Your Business Structure

Sole Proprietorship: Simplest form; income is reported on personal tax return.

Partnership: Income passes through to partners; requires filing of Form 1065.

LLC: Offers flexibility; can be taxed as sole proprietorship, partnership, or corporation.

S Corporation: Income and losses pass through to shareholders; requires Form 1120S.

C Corporation: Separate tax entity; taxed at corporate rates; requires Form 1120.

2. Register Your Business

Obtain an Employer Identification Number (EIN): Apply through the IRS website to get an EIN, which is needed for tax filings and hiring employees.

Register with State Agencies: Depending on your location, you may need to register with state tax authorities and obtain any necessary state-specific licenses or permits.

3. Maintain Accurate Financial Records

Bookkeeping System: Set up a reliable accounting system (software like QuickBooks, Xero, or FreshBooks).

Track All Income and Expenses: Document every transaction to ensure accurate reporting.

Maintain Receipts and Invoices: Keep all supporting documentation for expenses and income.

4. Understand Deductions and Credits

Business Expenses: Familiarize yourself with deductible expenses such as rent, utilities, salaries, and office supplies.

Startup Costs: Deduct up to $5,000 of startup costs in the first year, with any remaining costs amortized over 15 years.

Home Office Deduction: If you work from home, you may qualify for a home office deduction.

Employee Benefits: Deductions may include health insurance, retirement plan contributions, and other employee benefits.

Research and Development (R&D) Tax Credits: Explore credits available for research and innovation.

5. Plan for Self-Employment Taxes

Understand Your Tax Obligations: If you’re self-employed, you’ll need to pay self-employment tax in addition to income tax.

Quarterly Estimated Payments: Calculate and pay estimated taxes quarterly to avoid penalties. Use IRS Form 1040-ES for this purpose.

6. Implement Tax-Advantaged Retirement Plans

SEP IRA: Allows for higher contribution limits than traditional IRAs.

Simple IRA: Easier to set up and maintain, with lower contribution limits.

401(k): Consider a solo 401(k) if you are the only employee, or a traditional 401(k) plan if you have employees.

7. Review Tax Credits and Incentives

Small Business Health Care Tax Credit: If you provide health insurance, you might be eligible for this credit.

Work Opportunity Tax Credit (WOTC): Provides a tax credit for hiring individuals from certain target groups.

8. Plan for State and Local Taxes

Sales Tax: Register for and collect sales tax if applicable to your products or services.

State Income Tax: Understand your state’s income tax requirements and rates.

Local Taxes: Be aware of any city or county taxes that may apply.

9. File and Pay Taxes

Determine Filing Deadlines: Know the due dates for federal, state, and local tax filings.

Prepare Tax Returns: Use appropriate forms and schedules for your business structure.

Pay Taxes: Ensure timely payment of any taxes due to avoid penalties.

10. Stay Informed and Seek Professional Advice

Monitor Tax Law Changes: Tax laws frequently change, so stay updated on new regulations.

Consult a Tax Professional: Engage with a certified public accountant (CPA) or tax advisor who specializes in startups to ensure compliance and optimize tax strategies.

11. Keep Up with Tax Planning Throughout the Year

Regular Financial Reviews: Conduct periodic reviews of your financial statements and tax situation.

Adjust Tax Strategy as Needed: Make adjustments based on changes in revenue, expenses, or tax laws.

Plan for Future Growth: Anticipate tax implications of business expansion or changes in structure.

12. Document and Evaluate Your Tax Strategy

Maintain Records of Tax Strategies: Keep a record of tax planning strategies and their outcomes.

Evaluate Effectiveness: Regularly assess whether your tax strategy is meeting your goals and make necessary adjustments.

[kennak]

Pragmatic Engineer ニュースレターの無料号をおまけでお届けします。 私は毎号、エンジニアリング マネージャーやシニア エンジニアの視点から、ビッグテックやスタートアップに関連するトピックを取り上げています。 の 4 つのトピックのうち 1 つを取り上げます この記事では、本日の定期購読者限定のThe Pulse 号 。 全号を週に 2 回入手するには、 ここから購読してください 。 を調査し 10 月に、私たちはソフトウェア エンジニアによって設立された自���企業 、その記事が多くの読者の共感を呼びました。 この問題の後、私はブートストラップされた創業者からたくさんのメッセージを受け取りました。 多くのメッセージは「第 174 条の変更」と呼ばれるものに対する苦情でした。 ある創業者はこう言いました。 「数年前に施行された米国税法第 174 条の変更について聞いたことがありますか? この変化により、ブートストラップ型ソフトウェア ビジネスは完全に持続不可能になってしまいます。 ソフトウェア開発にかかる人件費も含め、研究開発にかかる費用は基本的に全額経費にすることはできません。 これらのコストは資産化され、5 年間、または米国外で労働が行われた場合は 15 年間で償却される必要があります。 この変化は完全に常軌を逸しているとしか言いようがありません。 私が話す人は皆同じことを言います。 他の自社企業との話し合いの中でこのことが話題になったかどうか知りたいのですが?」 私が調べてみたところ、ウォール・ストリート・ジャーナルと他の少数の報道機関が 昨年 3 月以来この変化を取り上げて いました。 それでも、手を差し伸べた創業者らは、この税制変更がどれほど大きな問題であるかについて、世間の認識が低いように感じられると語った。 、 さらに情報を集めるためにソーシャルメディアを利用したところ 米国のテクノロジー企業から驚くほど多くの苦情が寄せられました。 この号では、以下について説明します。 予期せぬ高額な税金が突然請求される 法律として成立させることを意図したことのない税制変更 なぜ大手テック企業やベンチャーキャピタルは警鐘を鳴らさなかったのでしょう？」 この変更が米国のテクノロジー企業とそこで働く開発者に与える影響 ソフトウェア労働力の強制償却が客観的に見て悪いのはなぜですか? 米国はスタートアップにとって競争力の低い場所であることに満足するだろうか？ 予期せぬ高額な税金が突然請求される 米国のソフトウェア企業の多くは、前年7月に発効した税制変更の影響で、2023年に驚くほど高額な税金を徴収した。これは、多くの中小企業が2022年の申告書を完成させるまで全く知らなかったものだ。 この変更は2022年12月に廃止（撤回）される予定であったため、多くの会計士はその理由から顧客に通知しなかった。 そのため、昨年 4 月に最初の納税期限��到来したとき、企業は驚きました。 S174 の修正は、世界の標準とは異なり、ソフトウェア エンジニアの雇用を、給与が支払われた年の直接経費として会計処理できなくなることを意味します。 以下は、変更前の最終課税年度からの変更の簡略化された例です。 「Acme Corp.」という架空の自社ソフトウェア ビジネスを考えてみましょう。 この会社は、SaaS サービスを運営して年間 1,000,000 ドルの収益を上げています。 同社は 5 人のエンジニアを雇用しており、各人に 20 万ドルを支払っています。 つまり人件費として100万ドル支払われます。 わかりやすくするために、サーバーやホスティングなどの他のコストは省略していますが、これらのコストも新しい研究開発ルールに該当する可能性があり、償却する必要があります。 では、この会社はどれくらいの課税利益を上げているのでしょうか？ 2021 年には、答えは利益ゼロになるでしょう。 2022 年の答えは、90 万ドルの利益でした(!!) 2022 年からソフトウェア エンジニアの人件費を 必要がある 5 年間で償却する ためです。 償却の仕組みは次のとおりです。 初年度は 10% 償却 20% を 2 年目から 5 年目に償却 6年目は10% これを詳しく見てみましょう: 売上高 100 万ドル、人件費 100 万ドルの企業に対する第 174 条の変更の影響。 この税金を支払うための現金 18 万 9,000 ドルが手元にない、自己資金で経営している小規模企業はどうなるでしょうか? 次の 2 つのオプションがあります。 比較的高い金利 (おそらく 10% 程度) でローンを組む。 中小企業が税金を支払うために個人ローンを利用する必要があると聞いたことがあります。  年間 200,000 ドルのソフトウェア エンジニアを解雇し、この節約で請求額を支払います。 米国の小規模テクノロジー企業では、ソフトウェアエンジニアの採用減少とソフトウェアエンジニアリングの人員削減がすでに起きている。 昨年1月、ウォール・ストリート・ジャーナルの記事で、政策アナリストのアレックス・ムレシアヌ氏は、 この税法変更により米国では約2万人のフルタイムのソフトウェア・エンジニアリングの雇用が失われると推定した 。 そして私は、米国企業がどのように打撃を受けているかについて、企業自身から直接聞いた、より現実的な説明を持っています。 企業は 2022 年に 9 万ドルの損失を計上しましたが、100 万ドルの利益に対して課税されます。 古いルールでは、 インフラスタートアップのグラントワークは、 採用数が減る。 この変化により2024年の 125万ドルを調達し、5人の従業員を雇用した新興企業は、 直面する可能性が高い。 計上されていない15万ドルの税金請求に 300 万ドルを調達し赤字で運営していたシード段階のスタートアップは、S174 の変更により黒字になったため、増税の予算を計上する必要があります。 別の米国企業は、税制変更を理由にインドで雇用していた23人のエンジニアを解雇した。 海外のソフトウェアエンジニアは15年でしか償却できません。 法律として成立させることを意図したことのない税制変更 では、「第 174 条の変更」とは何でしょうか? 理解するには数年前まで遡る必要があります。 2017年、当時のドナルド・トランプ大統領は、税法を全面的に見直して減税する「2017年減税・雇用法」に署名し、例えば最高税率を39.6％から37％に引き下げた。 この法案を厳格な予算規則で可決させるために、上院は「調整」と呼ばれるプロセスを採用し、増税を遅らせる税法の変更を加えた。 これらの遅れた増税により減税が「相殺」されました。 One of these changes was Section 174, set to come into effect 5 years later, in 2022. These parts deliver the blow by making it clear that software development costs need to be amortized over 5-15 years. Most experts expected Congress to push back the Section 174 amendment to a later date, or simply remove it. But Congressional negotiations to repeal the changes fell apart at the last minute in December 2022, meaning it became law.Why did Big Tech or VCs not raise the alarm?Why did we not hear the largest tech companies protesting the tax change? Actually, several did, but their protests failed to cut through on the news agenda.Large tech companies tend to speak up about issues like this via coalitions, trade associations, and lobbyists. Amazon, Microsoft, Intel, Ford, Lockheed Martin, and other US companies created the US R&D Coalition in 2018 to advocate in reversing this change. This group concludes:“[The Section 174 changes are] a dramatic shift in the tax treatment of business investments in research and innovation, and it will leave the United States with a system unlike any other in the industrialized world. By diminishing the near-term value of R&D expenditures, the Tax Cuts and Jobs Act will reduce incentives for companies to invest in the development of new products, ultimately hurting consumers and businesses alike.”私が年次報告書で見つけた内容に基づいて、S174 の変更が一部の企業にどのような影響を与えたかを次に示します。 Microsoft : 2023 年に 48 億ドルの追加税を支払いました 。同社はその年 720 億ドルの利益を上げたため、この増税は管理可能でした。 それにしてもすごい量ですね！ Netflix: 約 3 億 6,800 万ドルの追加納税 – これも年間 44 億ドルの利益で管理可能。 Google : Google はすでにほとんどのスタッフのソフトウェア開発費用を自主償却していたため、税金の変更は最小限でした。 これは、製品が一般公開される前に通過するマイルストーンである「技術的実現可能性」に達したすべてのプロジェクトが対象でした。 多額の現金を保有する企業にとって、この税制変更は不便ではあったものの、対処可能でした。 5 年間にわたって税額は均等になります。 5 年後、この種の会計では税制上の優遇措置が得られる可能性もあります。 VCが資金提供している企業はどうなるでしょうか？ 赤字企業にとって、この変更は大きな違いを生みません。 しかしこの変更は、損益分岐点に近いVCから資金提供を受けている企業に影響を与える。 VCから資金提供を受けているほとんどの企業は、損益分岐点に近づいており、予期せぬ税金を支払うのに十分な現金バッファーを持っている。 ただし、これらの企業は採用を削減するか、スタッフの解雇を検討する可能性があります。 米国のテクノロジー企業とそこで働く開発者への影響 第 174 条が存続し、すべての米国企業が ソフトウェア開発コストを 5 年間で償却しなけれ ばならないと仮定すると、これは初期段階の小規模テクノロジー企業に直ちに影響を与えるでしょう。 米国ではソフトウェア エンジニアの採用が減り、解雇が増加。 2023年と2024年に増税に直面する中小規模のテクノロジー企業は、開発者の雇用を減らすだろう。 キャッシュ フローの目的で社内開発者をベンダーに置き換えるために人員削減が発生する可能性があり、これにより次のような影響が考えられます。 Firing of non-US software engineers employed by US companies. The tax change is very hostile to software developers employed abroad: their wages need to be deducted over 15 years. Unless a US company has massive cash reserves, it now makes no sense to remotely employ or contract with individual software developers. An engineer shared how their company fired 23 developers employed in India because of Section 174.A boon for SaaS companies and vendors? US software companies now have a strong reason to buy, instead of build, software in-house. In February last year, we covered the trend of tech companies aggressively cutting vendor spend. This tax change greatly incentivizes US companies to increase vendor spend – and either not hire more devs, or let some go!It makes a lot less sense to incorporate tech startups in the US. Assuming there’s a choice to incorporate a startup in the US or somewhere else, then any other country makes so much more sense. In the first few years of a startup, it’s typical to make a loss while building something that might not work out. Thanks to the amortization rules, in the US this loss could turn into a taxable profit! Startup software IP will likely be moved out of the US. Foreign founded venture-backed startups have been overwhelmingly incorporated in Delaware, US, until now. The Delaware company would then hold the intellectual property (IP) of the startup. With the Section 174 changes, the simplest way to not be subject to US amortization requirements is to move the IP to a foreign subsidiary – and then this subsidiary can employ developers, without being subject to the 15-year amortization requirements. This is what newly founded VC-funded startups are doing, already! As usual, this is not legal or business advice. Consult a professional for guidance on this matter.Creative workarounds, like “inversion buying.” Say that you run a US company with a Canadian subsidiary, with most developers working in Canada. With Section 174 changes, Canadian developers need to be amortized over 15 years (!). A tempting workaround is to have the Canadian subsidiary buy the US company! Now this is a Canadian company, and Section 174 doesn’t apply to developers in Canada. However, such workarounds can be expensive and complicated from a tax perspective, due to Passive Foreign Investment Company (PFIC) rules. Still, plenty of founders are exploring setups like this.テクノロジー企業は現在、研究開発クレジットを理解し、使用することを強いられています。 S174 修正案は、ほぼすべてのソフトウェア開発を研究開発として強制的に��類します。 研究開発クレジットによって税額が相殺されるという利点もありますが、それは部分的にのみです。 研究開発税額控除の対象となる研究開発費は、通常、すべての研究開発費の一部です。 画像出典: Aprio Insights 税額控除と第 174 条の詳細については、Gusto が 第 174 条の納税義務計算ツール を作成しました。 この変更の影響を受けるビジネスを運営している場合は、いつものように専門家のアドバイスを受けることを検討してください。 第 174 条が存続すれば、米国のソフトウェア企業全体のイノベーションは打撃を受けることになる。 この税制変更により、多額の現金を持たないソフトウェア会社は 投資を減らす 研究開発への ことが奨励されています。 あるいは、海外に移住することもできます。 しかし、この変化は小規模なソフトウェア会社にとって悪いだけではありません。 それは最大の企業でさえも痛手となるため、マイクロソフトとアマゾンもその逆転を主張しているのです。 ソフトウェア労働力の強制償却が客観的に見て悪いのはなぜですか? 減価償却（減価償却とも呼ばれます）の概念は次のとおりです。 SaaS ビジネスのトラフィックを処理するために、強力なサーバーを 2,000 ドルで購入したとします。 その場で2000ドル支払います。 ただし、このサーバーの予想寿命は 4 年で、その後は交換する必要があります。 したがって、このサーバーから毎年約 500 ドル相当の「価値」を得ているため、会計年度ごとにこのサーバーの価値の 4 分の 1 を 4 年目まで償却 (減価償却) する、と主張するのが合理的です。 This kind of depreciation is sensible, as you could sell your server for around $1,000 after two years (assuming that is how its value depreciation.) Tax authorities in different countries have come up with depreciation frameworks that businesses follow along these lines. For example, in the US, the Financial Accounting Standards Board (FASB) created the Generally Accepted Accounting Principles (GAAP) provisions, which include a framework on how to deal with depreciation.Amortizing software development over years makes sense – but only in some cases. If you have launched a software product, have customers, and you can forecast demand for this product pretty accurately, then investing developer hours to keep this SaaS running feels similar to buying hardware. The software engineer could build a new feature for the SaaS which generates revenue for years to come. So there is some argument to treat software development akin to buying a server.But is comparing physical goods to software, accurate? Take a company that buys a server office it plans to use for 20 years. After a massive one-off investment, the only cost is maintenance, which is a pretty minimal cost.Now take the example of creating software to generate revenue for 20 years. If you do barebones maintenance, the software becomes obsolete in a year or two! You need to keep adding new features and keep up with the competition. As you add more features, you run into tech debt and architecture issues, so you refactor the software and within a few years you rewrite the whole thing!Building software is like continuously renovating – and rebuilding – a property. While it is tempting to see why an accountant would want to treat software development amortized like physical goods, this is simply not the reality of how software products behave, or are maintained.Before Section 174, companies could choose how they categorized software developers, and could opt into deducting costs. This is what stable and highly profitable businesses like Google have done: for software products in production (and making money) it deducted developer costs over 5 years. For pre-launch projects, Google simply expensed those developers. This is the sensible way to run a software business, after all!Google employing lots of devs in Switzerland starts to make a lot more sense, especially now. Ever wondered why Google has such a large software engineering center in Switzerland – despite the high cost of software engineers within Europe? Switzerland has a very powerful research and development incentive: the country allows expensing 135% of R&D-related salaries in the year they are incurred. Switzerland’s taxation is pretty much the polar opposite of that of the US with Section 174. Is Section 174 stays, I would not be surprised if some US companies considered following Google’s lead and explore setting up engineering offices in this country.Will the US be content being a less competitive place for startups?All founders whom I talked with hoped Congress would revert this disastrous tax code change, given its devastating impact on tech startups. However, this has not happened – and it’s unclear if it will.Founders have been trying to get the attention of Congress: sending a letter signed by 1,000+ software businesses, and creating coalitions like the American Innovators Coalition. Another group formed in March this year is the Small Software Business Alliance, created by indie SaaS founder Michele Hansen, supported by over 600 small software company founders. I asked Michele why she thinks the general public isn't aware of the threat to US companies. She said:「1. 長年にわたり、税制変更は中小企業ではなく大企業に影響を与えるという認識があった。 2. 税制問題は一般の人々にとって退屈なものです。 このようなニュースが主流メディアに浸透するには、大量解雇などの強い社会的影響が必要です。 3. 第 174 条は決して発効する予定ではなく、発効前に修正されるだろうと広く想定されていました。 そのため、解決する可能性のある問題にはほとんど関心がありませんでした。」 しかし、ミケーレ氏は、希望を持つ理由があると語った。 議会は研究開発費に関する第174条の変更を撤回するという合意に達したようだ。 議員らは現在、 この取引に資金を提供する方法を模索して いる。 ある国がソフトウェア開発の競争力を低下させることは、明らかに他の国に利益をもたらします。 S174 修正条項のおかげで、 外で スタートアップ資金の調達を含め、米国 テクノロジー企業を設立することははるかに魅力的です。 それでも、米国は長い間テクノロジーの世界的なイノベーションの中心地であり、この国が技術革新を実現すれば、他の国々が追いつくかもしれない。 しかし、これが世界全体のイノベーションにとって有益であるとは私には思えません。 に感謝します。 Michele Hansen と Jacek Migdał このセクションの草案について洞察を与え、レビューしてくれた

The Pulse: 米国企業は第 174 条によ​​りエンジニアの雇用が減りますか? - 実践的なエンジニア

[metamoonshots]

In its Aug. 1 monetary outcomes, enterprise intelligence agency MicroStrategy mentioned it acquired substantial Bitcoin throughout Q2 2023. Andrew Kang, Chief Monetary Officer at MicroStrategy, said: “The addition within the second quarter of 12,333 bitcoins [is] the biggest enhance in a single quarter since Q2 2021. We effectively raised capital… and used money from operations to proceed to extend bitcoins on our stability sheet.” In a separate presentation, the agency mentioned that the 12,333 BTC it purchased was bought for $347 million at a median of $28,136 per Bitcoin. Nevertheless, these numbers solely symbolize the corporate’s newest additions, not the entire quantity of Bitcoin it acquired. MicroStrategy mentioned that, as of July 31, 2023, it had acquired 152,800 BTC for $4.53 billion or $29,672 per Bitcoin. Regardless of these excessive estimates, the corporate mentioned that the carrying worth (the unique value of the asset, much less any depreciation, amortization or impairment prices) of its Bitcoin was simply $2.3 billion. That quantity displays cumulative impairment losses of $2.196 billion since MicroStrategy’s first buy and a median carrying quantity per Bitcoin of $15,251. MicroStrategy famous elsewhere that Bitcoin and its personal MSTR inventory have outperformed quite a few different indexes and property. MSTR has gained 254% because it adopted its Bitcoin technique in August 2020, whereas Bitcoin itself has gained 145% since that date. Through MicroStrategy MicroStrategy in any other case reported whole revenues of $120.4 million in Q2 2023, which represents a 1% lower in income year-over-year. Bitcoin within the greater image Kang additionally positioned MicroStrategy’s purchases inside broader trade developments, reminiscent of growing curiosity from institutional traders and regulatory readability round Bitcoin. Kang additionally mentioned that MicroStrategy is seeing progress concerning Bitcoin accounting practices. In Could, the corporate submitted a letter to the Monetary Accounting Requirements Board (FASB) expressing assist for a good worth accounting for crypto property. It mentioned this is able to enable it to supply a “extra related view” of its Bitcoin holdings. In its firm profile, Microstrategy referred to as Bitcoin a “reliable retailer of worth” and described Bitcoin acquisition as one in all its two essential methods alongside its enterprise software program enterprise. UPDATE: Aug. 2, 2023, 9AM – MicroStrategy announced the sale of as much as $750 million of its Class A inventory on Aug. 1 doubtlessly to fund further Bitcoin purchases. The publish MicroStrategy made largest Bitcoin purchase since 2021 in Q2 2023 amid slight revenue decrease appeared first on CryptoSlate.