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ios – FFmpeg Arthenica at all times encodes with x265 Main10 profile


I am utilizing FFmpeg-Package (Arthenica) for iOS to compress movies utilizing the libx265 encoder. I am constructing FFmpeg with a customized configuration script:

export CUSTOM_CONFIG="--disable-indevs 
  --disable-outdevs 
  --disable-hwaccels 
  --enable-videotoolbox 
  --disable-protocols 
  --enable-protocol=file,fd,saf,async 
  --disable-decoders 
  --enable-decoder=${ENABLE_DECODER_LIST} 
  --disable-encoders 
  --enable-encoder=${ENABLE_ENCODER_LIST}"

export CUSTOM_CONFIG_IOS=${CUSTOM_CONFIG}
  ./ios.sh --enable-ios-videotoolbox --enable-lame --enable-libaom  --enable-libtheora --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libxml2 --enable-opencore-amr --enable-openh264 --enable-opus --enable-twolame --enable-x264 --enable-x265 --enable-gpl

Then I run FFmpeg with the next instructions:

-y -hide_banner -i enter.MOV -vcodec libx265 -x265-params profile=most important output.mov
-y -hide_banner -i enter.MOV -vcodec libx265 -x265-params profile=main10 output.mov

Nonetheless, whatever the profile I set, the output at all times finally ends up being encoded with the Main10 profile.

Right here’s the log output:

x265 [info]: HEVC encoder model 3.4
x265 [info]: construct information [Mac OS X][clang 16.0.0][32 bit][noasm] 10bit
x265 [info]: utilizing cpu capabilities: none!
x265 [info]: Important 10 profile, Stage-5 (Important tier)

Evidently the FFmpeg construct solely helps 10-bit encoding. I would like to have the ability to encode with totally different profiles (most important, main10, and so on.), in addition to to construct libx265 in a manner that helps 8-bit + 10-bit + 12-bit encoding (unified 64-bit construct), as like as the identical command executes for MacOS.

x265 [info]: HEVC encoder model 4.1+1-1d117be
x265 [info]: construct information [Mac OS X][clang 16.0.0][64 bit] 8bit+10bit+12bit
x265 [info]: utilizing cpu capabilities: NEON Neon_DotProd Neon_I8MM
x265 [info]: Important profile, Stage-2.1 (Important tier)

How can I appropriately configure and construct FFmpeg and libx265 with Cellular FFmpeg to help a number of bit depths and permit setting totally different profiles through -x265-params?

Is the UK financial system extra R&D intensive than we’ve thought? – Comfortable Machines


1. On the discrepancy between ONS and HMRC estimates of enterprise R&D.

Within the UK, there are two methods by which the full quantity of enterprise R&D (BERD) is measured. The Workplace for Nationwide Statistics conducts an annual survey of enterprise, by which a pattern of corporations is requested to report how a lot R&D has been carried out. In the meantime corporations can report what R&D they’ve carried out to the taxman – HMRC – as a way to declare R&D tax credit, which in accordance with circumstances could be a discount of their legal responsibility for company tax, or an precise money cost. In recent times, the 2 measures of enterprise R&D have more and more diverged, with considerably extra R&D expenditure being claimed for tax credit than is reported within the BERD survey.

Is the UK financial system extra R&D intensive than we’ve thought? – Comfortable Machines

The divergence between HM Income and Customs (HMRC) and Enterprise enterprise analysis and improvement (BERD) estimates of analysis and improvement (R&D) expenditure. Supply: ONS.

The ONS has been wanting into this divergence, and has just lately printed a word which concludes that the first motive for the discrepancy is an undersampling of the small enterprise inhabitants. On this foundation, it has adjusted its earlier estimate for enterprise R&D considerably upwards – in 2020, the revision is from £26.9 bn to £43 bn. In future years, ONS will introduce improved, extra sturdy, methodologies that may embody a wider vary of SMEs within the pattern they survey.

In precept, there might be two doable causes for the rising divergence between the full enterprise R&D recorded by the ONS BERD survey and the quantities underlying claims to HMRC for R&D tax credit:

a. The incentives of R&D tax credit have brought about companies to stretch the definition of R&D to allow them to get cash for actions which are a part of regular enterprise (e.g. market analysis, figuring out tips on how to use new tools). That is exacerbated by the expansion of an trade of consultants providing their providers to corporations to assist them declare this cash (in return for a %).

b. The ONS survey of corporations (the BERD survey) has systematically undersampled a inhabitants of small and medium enterprises (SMEs), which prove to have extra R&D exercise than beforehand believed.

In favour of (a) – the discrepancy between the 2 measures hasn’t been fully static, as you’d count on if it was merely a query of lacking a inhabitants of corporations who had at all times been doing R&D at a relentless charge, however who’ve solely simply been found. The hole has risen from £7.3 bn in 2014, to £16.6 bn in 2018. So for this rationalization to carry, we have to imagine not solely that there’s an current inhabitants of SMEs finishing up R&D that has beforehand been undetected, however that this inhabitants has been considerably rising. Is R&D progress within the SME sector at a charge of £2.3 bn a 12 months believable? I’m unsure.

Furthermore, the incentives for stretching the definition of R&D to assert free cash are apparent. HMRC settle for that some claims are outright fraudulent, estimating that 4.9% of the price of the scheme is attributable to error and fraud. However there’s a giant gray space between outright fraud and inventive interpretation of the “Frascati” definitions of R&D.

ONS argues in favour of (b), backing this up with an in depth comparability of the microdata from the ONS survey and HMRCs returns. So as to add some anecdotal help, work in Higher Manchester in collaboration with an information science consultancy does appear to have recognized a inhabitants of progressive SMEs in GM which has beforehand remained invisible, within the sense that they’re corporations who don’t have interaction with universities or with Innovate UK.

In fact, the true reply might be some combination of the 2. We’ll study extra as soon as the brand new methodology has produced an entire information set figuring out the sectors and geographical places of R&D performing corporations.

2. Coverage implications

Figures for whole R&D spending (together with each enterprise and public sector R&D) as a proportion of GDP present a helpful measure of the general analysis depth of the UK financial system and type the premise for worldwide comparisons. The earlier determine for R&D depth – about 1.7% – put the UK between the Czech Republic and Italy. The brand new estimates recommend a revised determine of two.4%, which might put the UK roughly on a par with Belgium, barely above France, however behind the USA and Germany, and nonetheless a great distance behind leaders like Korea and Israel. After all, when making these worldwide comparisons, a pure query is how correct are the R&D statistics in these different nations. It is a good query that might be investigated by OECD, who collate worldwide R&D statistics.

The worldwide comparability has pushed a goal for R&D depth that the federal government dedicated to – that it could obtain an R&D depth equal to the OECD common. On the time when the goal was formulated this common was certainly equal to 2.4%. Nevertheless, the OECD common is a shifting goal since different nations are rising their very own R&D – it’s now above 2.5%. One can even ask whether or not a goal to attain worldwide mediocrity is stretching sufficient.

There are extra basic points with the concept of getting an R&D depth goal in any respect. One quirk of expressing the goal as a % of GDP is that one can obtain it by driving down the denominator; actually GDP progress within the UK has been disappointing for the final 12 years, because the Prime Minister has reminded us. One might argue {that a} numerical goal for R&D is bigoted and one ought to focus extra on the instrumental outcomes one desires to attain from the analysis – larger progress, extra speedy and price efficient progress in direction of web zero, higher inhabitants well being outcomes and so forth. As I wrote myself just lately in my survey of the UK R&D panorama:

“An R&D goal needs to be considered not as an finish in itself, however as a way to an finish. We should always begin by asking what sort of financial system do we want, if we’re to fulfill the large strategic targets that I mentioned within the first a part of this collection. Given a clearer view about that, we’ll have a greater understanding the required fraction of nationwide sources that we should always dedicate to analysis and improvement. I don’t know if that will produce the precise determine of two.4%, however I wouldn’t be stunned if it was considerably larger.”

Maybe probably the most problematic implication of a BERD improve is the enduring puzzle that productiveness progress stays very gradual. This further, beforehand unrecorded R&D, doesn’t appear to have translated into productiveness progress as we’d count on.

This raises the broader query of why we predict the federal government ought to help enterprise R&D in any respect, whether or not by R&D tax credit or by different means. The classical argument is that non-public sector R&D results in wider advantages from the financial system that aren’t captured by the corporations that make the investments, so within the absence of presidency corporations will make investments much less in R&D that will be socially optimum. This results in the query of whether or not all types of R&D, in all types of firm (e.g. giant and small) result in equal levels of wider spillover results (and the identical query will be requested of intangible investments extra typically). If the sorts of R&D that are actually being revealed with the brand new methodology do have smaller spillovers than different sorts, one would possibly ask what sort of interventions might enhance these.

3. Political implications

As others have noticed, the chief hazard of the revision is that in instances of fiscal retrenchment, the federal government might declare “mission achieved” and delay or cancel will increase in public R&D. This hazard appears very actual given the route of the present authorities. The opposition, however, has referred to as for an R&D goal of three% of GDP, so there may be loads of room there.

There’s an argument that the revision means that public R&D is much more efficient than we thought in producing non-public sector R&D – the leverage impact is stronger than we thought. For this argument to be convincing, we’d want to grasp the diploma to which the businesses doing this R&D are related to the broader innovation system. Nevertheless it doesn’t then help the broader argument for R&D as a driver of productiveness progress – we’ve got the R&D depth we aspired to, so why aren’t we seeing the advantages within the productiveness figures?

There are doable arguments that our focus in enterprise R&D has been an excessive amount of on the large incumbents – the GSKs and Rolls Royces – whose R&D could be very seen. Then again, this connects to the long-running query of why we don’t have extra of these massive incumbents? At this level, we should always recall that there are solely two UK firms within the world top-100 of R&D performers – AstraZeneca and GSK. So why aren’t a few of these beforehand unseen R&D intensive firms scaling as much as turn into the brand new massive gamers?

There’s a lot but to grasp right here.

AI Prices Are Accelerating — Right here’s Preserve Them Beneath Management

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Cloud utilization continues to soar, as do its related prices — significantly, of late, these pushed by AI. Gartner analysts predict worldwide end-user spending on public cloud providers will swell to $723.4 billion in 2025, up from slightly below $600 billion in 2024. And 70% of executives surveyed in an IBM report cited generative AI as a important driver of this enhance.

On the identical time, China’s DeepSeek made waves when it claimed it took simply two months and $6 million to coach its AI mannequin. There’s some doubt whether or not these figures inform the entire story, but when Microsoft and Nvidia’s still-jolted share costs are any indication, the announcement woke the Western world as much as the necessity for cost-efficient AI programs.

So far, corporations have been capable of deal with mounting AI prices as R&D write-offs. However AI prices — particularly these related to profitable merchandise and options — will ultimately hit corporations’ value of products bought (COGS) and, consequently, their gross margins. AI improvements have been at all times destined to face the chilly scrutiny of enterprise sense; DeepSeek’s bombshell announcement simply shortened that timeline.

Identical to they do with the remainder of the general public cloud, corporations might want to handle their AI prices, together with each coaching and consumption prices. They’ll want to attach AI spending with enterprise outcomes, optimize AI infrastructure prices, refine pricing and packaging methods, and maximize the return on their AI investments.

How can they do it? With cloud unit economics (CUE).

What’s cloud unit economics (CUE)?

CUE includes the measurement and maximization of cloud-driven revenue. Its basic mechanism is connecting cloud value information with buyer demand and income information, revealing probably the most and least worthwhile dimensions of a enterprise and thus displaying corporations how and the place to optimize. CUE applies throughout all sources of cloud spending, together with AI prices.

The inspiration of CUE is value allocation — organizing cloud prices in accordance with who and/or what drives them. Frequent allocation dimensions embody value per buyer, value per engineering group, value per product, value per function, and price per microservice. Firms utilizing a contemporary value administration platform typically allocate prices in a framework that mirrors their enterprise construction (their engineering hierarchy, platform infrastructure, and so on.).

Then, the center of CUE is the unit value metric, which compares value information with demand information to point out an organization their all-in value to serve. For instance, a B2B advertising and marketing firm would possibly wish to calculate its “value per 1,000 messages” despatched through its platform. To do that, it must monitor its cloud prices and the variety of messages despatched, feed that information right into a single system, and instruct that system to divide its cloud prices by its messages and graph the end in a dashboard.

For the reason that firm began with value allocation, it may then view its value per 1,000 messages by buyer, product, function, group, microservice, or no matter different view it deemed reflective of its enterprise construction.

The outcomes:

  • Versatile enterprise dimensions by which they’ll filter their unit value metric, displaying them which areas of their enterprise are driving their cloud prices
  • An illuminating unit value metric that exhibits them how effectively they’re assembly buyer demand
  • The power to make focused effectivity enhancements, like refactoring infrastructure, tweaking buyer contracts, or refining pricing and packaging fashions

CUE within the AI age

Within the CUE mannequin, AI prices are only one extra supply of cloud spending that may be included right into a enterprise’s allocation framework. The way in which that AI corporations disseminate value information remains to be evolving, however in precept, value administration platforms deal with AI prices in a lot the identical means as they deal with AWS, Azure, GCP, and SaaS prices.

Trendy cloud value administration platforms allocate AI prices and present their effectivity affect within the context of unit value metrics.

Firms ought to allocate their AI prices in a handful of intuitive methods. One can be the aforementioned value per group, an allocation dimension frequent to all sources of cloud spending, displaying the prices that every engineering group is accountable for. That is significantly helpful as a result of leaders know precisely who to inform and maintain accountable when a specific group’s prices spike.

Firms may also wish to know their value per AI service sort — machine studying (ML) fashions versus basis fashions versus third-party fashions like OpenAI. Or, they might calculate their value per SDLC stage to know how an AI-powered function’s prices change because it transitions from growth to testing to staging and at last to manufacturing. An organization may get much more granular and calculate its value per AI growth lifecycle stage, together with information cleaning, storage, mannequin creation, mannequin coaching, and inference.

Zooming out from the weeds a bit: CUE means evaluating organized cloud value information with buyer demand information after which determining the place to optimize. AI prices are only one extra supply of cloud value information that, with the proper platform, match seamlessly into an organization’s general CUE technique.

Avoiding the COGS tsunami

As of 2024, solely 61% of corporations had formalized cloud value administration programs in place (per a CloudZero survey). Unmanaged cloud prices quickly grow to be unmanageable: 31% of corporations — just like the portion who don’t formally handle their prices — undergo main COGS hits, reporting that cloud prices eat 11% or extra of their income. Unmanaged AI prices will solely exacerbate this development.

Right this moment’s most forward-thinking organizations deal with cloud prices like some other main expenditure, calculating its ROI, breaking that ROI down by their most crucial enterprise dimensions, and empowering the related group members with the information wanted to optimize that ROI. Subsequent-generation cloud value administration platforms supply a complete CUE workflow, serving to corporations keep away from the COGS tsunami and bolster long-term viability.

Kia & LG Electronics Associate to Showcase New PBV Ideas for Work & Play



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  • Kia and LG Electronics cooperate to current idea fashions for cellular skilled and leisure areas primarily based on Kia’s Platform Past Cars (PBVs)
  • The PV5 Spielraum Studio idea for cellular work and the PV5 Spielraum Glow cabin idea for out of doors actions debut on the 2025 Seoul Mobility Present
  • Kia and LG are collaborating to launch the idea fashions within the second half of 2026

Kia Company and LG Electronics at the moment introduced a partnership to collaborate on the implementation of mobility area options primarily based on PBV (Platform Past Car) know-how.

The businesses signed a Memorandum of Understanding (MOU) on the Kia pavilion on the 2025 Seoul Mobility Present, held at KINTEX in Goyang, South Korea, and unveiled idea fashions for cellular work and leisure areas that incorporate superior dwelling home equipment into Kia’s PBVs.

The MOU signing ceremony was attended by Gained-Jeong Jeong, Government Vice President and Head of Korea Enterprise Division at Kia, and Lyu Jae-cheol, president of the LG House Equipment Answer Firm.

The settlement brings collectively Kia’s PBV know-how and LG’s experience in AI options. The businesses purpose to supply custom-made area experiences for customers, tailor-made to totally different existence and work wants, by integrating superior dwelling home equipment into PBVs. This may allow customers to remodel the automobile into a personalised workplace, studio, lounge, and many others.

“By providing mobility area options that mix cars with dwelling home equipment, we purpose to guide a transformative shift in prospects’ existence,” mentioned Gained-Jeong Jeong, Government Vice President and Head of Korea Enterprise Division at Kia. “This partnership with LG Electronics advances the core worth of PBVs, contributing to a brand new mobility paradigm the place autos evolve into personalised areas for dwelling and dealing.”

PV5 Spielraum ideas

Kia and LG are showcasing two PV5 Spielraum idea fashions on the Kia pavilion throughout the 2025 Seoul Mobility Present, held from April 4 to 13. The phrase ‘Spielraum’ — German for ‘play area’ — displays the idea of versatile mobility environments.

  • Spielraum Studio idea: The Spielraum Studio idea is geared toward solo entrepreneurs who journey ceaselessly, requiring each workspace and storage. It options LG’s AI-powered dwelling home equipment, resembling its modular Stylers[1], sensible mirrors, and occasional machines, that are built-in to optimize the PV5’s inside. The AI system can monitor the consumer’s enterprise schedule, calculate the remaining journey time to the vacation spot, and advocate equipment settings accordingly.
  • Spielraum Glow cabin idea: The Spielraum Glow cabin idea is designed to cater to the rising demand for automotive picnic experiences. It contains home equipment resembling fridges, lightwave ovens, and wine cellars, seamlessly supporting a variety of out of doors leisure actions. Every equipment has MoodUP™ panels[2] that regulate shade primarily based on the consumer’s preferences, offering a singular expertise.

The 2 corporations are working collectively to convey the idea fashions to market within the second half of 2026. With this settlement as a place to begin, additionally they plan to cooperate in creating superior dwelling home equipment and AI options that may streamline and improve on a regular basis duties.

[1] LG Styler is LG’s clothes care answer designed for garment caring, specializing in sanitization and deodorization via TrueSteam™ Expertise. It additionally reduces wrinkles with its shifting hanger and steam.

[2] The MoodUP panel is a characteristic in LG MoodUP™ fridges that enables customers to vary the colour of the door panel through LG ThinQ™ app, enabling the customization of colours to match the popular environment or temper.

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.NET 9 Maui WebView Embedded WebPage iOS Hyperlinks


Let me preface this by saying I used to be requested to take a look at this undertaking and I’ve basically two days to finish it and have not carried out any cell growth in years. I have been requested to construct a cell iOS utility that wraps certainly one of our different web sites. There’s a requirement that the hyperlinks throughout the nested webpage open throughout the utility and do not attempt to load into the default internet browser. I’ve tried subscribing to the OnNavigating and the OnNavigated occasions however it seems that nothing is occurring once I try this. It doesn’t matter what I attempt it seems that slightly black bar with the hyperlink textual content seems within the app however then disappears as soon as I click on wherever else.

[![Screenshot][1]][1]

That makes me assume that the hyperlink on the nested web page is attempting to open a brand new tab or browser (which is what it might do when displayed on Safari) however I can not appear to determine how you can catch this occasion so I can redirect the WebView supply. I’m utilizing the next code for my WebView. Please assist.


namespace Views;

public partial class HomePage : ContentPage
{
    public HomePage()
    {
        InitializeComponent();
        HomeWebView.Navigated += OnNavigated;
    }

    /// 
    /// WebView steps bakc one web page (like an online browser again button).
    /// 
    /// 
    /// 
    personal void OnBackButtonClicked(object sender, EventArgs args)
    {
        if (HomeWebView.CanGoBack)
        {
            HomeWebView.GoBack();
        }
       
    }

    /// 
    /// Redirects the online view to the primary MyApps web page.
    /// 
    /// 
    /// 
    personal void OnHomeButtonClicked(object sender, EventArgs args)
    {
        HomeWebView.Supply = "https://myapps.com";
    }

    /// 
    /// Routes the consumer to the about web page.
    /// 
    /// 
    /// 
    personal void OnAboutButtonClicked(object sender, EventArgs args)
    {
        Shell.Present.GoToAsync("//aboutPage");
    }

personal void OnNavigated(object sender, WebNavigatedEventArgs e)
    {
        //The next code modifications the goal of all of the hyperlinks in _self
        HomeWebView.EvaluateJavaScriptAsync(@"(operate() {
            var hyperlinks = doc.getElementsByTagName('a');
            for (var i = 0; i < hyperlinks.size; i++)
            {
                hyperlinks[i].setAttribute('goal', '_self');
            }
        })()");
    }

}


  [1]: https://i.sstatic.internet/UWBK5RED.png