This is interesting, within the broader context of Meta’s ongoing and massive investment into AI data center projects.

Today, hardware provider Arm has announced a new partnership with Meta, which will see Meta work with Arm to establish expanded systems to help power recommendations across its apps.

As explained by Arm:

“Arm and Meta have announced a strategic partnership to scale AI efficiency across every layer of compute – spanning AI software and data center infrastructure – to enable richer user experiences to billions of people worldwide. From milliwatt-scale devices powering on-device intelligence to megawatt-scale systems training the world’s most advanced AI models, the collaboration will enable AI across multiple types of compute, workload, and experiences that power Meta’s global platforms.”

So rather than relying on just its own infrastructure and evolving tech, which also includes the development of its own AI chips, Meta’s partnering with Arm to power its recommendation engine, specifically, with Arm’s various elements.

“Meta’s AI ranking and recommendation systems – which power discovery and personalization across Meta’s family of apps, including Facebook and Instagram – will leverage Arm’s Neoverse-based data center platforms to deliver higher performance and lower power consumption compared to x86 systems.”

It’s interesting to see Meta outsourcing this critical element of its systems to a third-party provider, though there’s nothing to suggest that Arm will have direct input into these elements, and/or how Meta’s ranking systems work.

The partnership is based on infrastructure, and empowering Meta to optimize its systems. But even so, given the critical nature of these elements, it seems like something that Meta would want to keep in-house as much as possible.

I mean, Meta is also investing hundreds of billions into AI infrastructure, and building for the future of “superintelligence.” So it does have a lot of processes to compute, alongside the daily activities of its billions of users, and as such, it’s not like Meta can’t use the help. But again, given that this does specifically refer to AI ranking and recommendation systems, it seems worthy of note in regards to the evolution of Meta’s systems.

Does that mean that Meta’s AI ranking will now be dependent on a third-party? Does it mean that Meta’s ranking systems will improve under this new process?

Arm does also note that the partnership will produce “measurable gains in inference efficiency and throughput,” with insights on such to be shared with the open source community.

So it could end up providing more insight into how Meta’s ranking systems work, at least in some capacity, and it’ll be interesting to see how this helps Meta evolve and upgrade its rankings to improve the relevance of the user experience.

Either way, it’s another indicator of Meta’s ever-sprawling tech empire, and the various ways that it’s looking to expand its AI capacity however it can.

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YouTube is looking to help brands better understand the broader impact of their YouTube content, with the development of a new “Brand Pulse Report,” which will provide an AI-powered summary of your expanded YouTube performance, mention and impact data.

As you can see in the above example, YouTube’s Brand Pulse Report will provide more info into the performance of your channel, and how your paid and organic efforts are contributing.

But it also goes further than that.

As explained by YouTube:

“The brand pulse report will use all-new data, powered by Google AI, to provide actionable insights that help you understand the full presence of your brand’s content on YouTube. The report uses first-of-its-kind, multi-modal AI to evaluate your brand presence across YouTube by detecting brand mentions via visuals (brand logos, product shots, etc.) and language (audio, video titles, etc.). So, if a creator uses or mentions your product in passing, we recognize it and capture it.”

So now, you’ll be able to get an expanded view of your brand performance across the app, including untagged mentions and appearances in other clips.

How accurate that is, and how good the system does at detecting such, will likely vary. But with visual recognition processes advancing, it could be a valuable update to your content tracking, which will help you get a better sense of your broader content impact.

The report also includes data on your total unique viewers, share of watch time and historical content performance.

It’ll also show you how your paid promotion efforts drive organic views, which YouTube says is an underrated element:

The additional data notes could provide significant assistance in your planning, and mapping out a more effective YouTube content strategy.

But it’s not available to everyone just yet.

YouTube says that its Brand Pulse Report is currently only available to select advertisers, with further expansion planned “in the coming months.”

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Instagram’s trying out another way to help creators arrange brand sponsorship deals, this time via downloadable PDF summaries of your account stats that you can share with prospective business partners.

As you can see in this example (shared by social media expert Matt Navarra), Instagram’s developing a new option that would enable you to share account and content performance data in a simplified summary, which you can then pass on to third parties.

That could be of particular help for Reels creators, by showcasing specific Reels view and engagement stats, which could boost advertiser interest. Much like TikTok, more brands are seeking creator assistance with Reels because it takes a level of creative nous and understanding of the format to maximize Reels performance, which makes experienced creators a strong option to help tap into this stream.

And with Reels now accounting for 50% of all time spent on Instagram, it’s a critical consideration, which could further enhance the value of this option.

It’s the latest in Meta’s broader effort to provide more means to help creators generate revenue from their on-platform efforts, with

Instagram’s also added on-profile “Creator Insights,” which provides a snapshot of account performance (over the last 30 days), as well as data on creator profiles in its Creator Marketplace, which show how that creator’s past brand collaborations have performed.

Meta also added content recommendations within its Partnership Ads Hub in Ads Manager earlier this year, which highlight relevant organic content that mentions a brand, and is also likely to perform well as a paid promotion.

These expanded offerings will ideally give creators more ways to showcase their skills and expertise, and what they can offer in brand deals, ultimately leading to more opportunity across both Facebook and IG.

Meta further notes that partnership ads can drive significantly more purchase activity.

Worth noting in your process.

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LinkedIn will now integrate more audience engagement data from parent company Microsoft, in order to expand LinkedIn’s ad targeting capacity, based on expanded digital tracking cues.

Last week, LinkedIn announced an update to its Terms of Service in order to cover expanded use of user data for its AI tools, as well as an expansion of the member data that it shares with Microsoft for Microsoft’s own ad targeting and promotions.

Essentially, LinkedIn will now share your profile and activity data with Microsoft, in order to enable Microsoft to better target its own promotions based on the same.

And LinkedIn will now also be better enabled to utilize the opposite as well.

LinkedIn’s added a related explainer in its overview of how businesses can use third party data to target ads on LinkedIn which explains how LinkedIn advertisers will now also be able to reach users based on data insights from Microsoft.

As per LinkedIn:

“Outside of the Designated Countries, the U.K., and California, LinkedIn also receives data from its affiliate, Microsoft, about activity on their and their advertisers’ sites and apps, including through use of technology similar to the LinkedIn Insight Tag. LinkedIn can use this information to improve its ability to reach an advertiser’s target audience as well as to improve ad performance and provide aggregate reports about advertising campaign performance to advertisers.”

So basically, LinkedIn is now integrating more data from Microsoft, via Microsoft’s own performance and data tracking measures, in order to provide expanded targeting options and insight for your campaigns.

Which could be valuable. Microsoft has its own Universal Event Tag (UET) for ad performance tracking, which records what customers do on various websites, and shares that information back to Microsoft. That enables Microsoft to track conversion activity and other behavioral data, which LinkedIn will seemingly now be able to incorporate into its own ad offering.

Microsoft also has additional ad engagement and data tracking measures that will feed more data into LinkedIn, which could facilitate expanded opportunities for your campaigns.

It’s more data, and more data is always better, and it may end up being a helpful addition in your process.

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OpenAI has published a new overview of how people are using ChatGPT, and how usage of its conversational AI tool is evolving over time, which provides some interesting insight into what people are looking to use the tool for, and how that relates to broader trends.

The study is based on an analysis of 1.5 million conversations in the app over the last three years, providing a huge pool of usage data to determine key trends.

You can download the full report for yourself here, but in this post, we’ll take a look at some of the key notes.

First off, the report looks at the overall growth in usage of ChatGPT, which has risen from a million active users in late 2022, to 700 million weekly active users today.

That’s no surprise, with ChatGPT quickly becoming synonymous with AI usage in general, driving more and more interest in the tool.

The data also shows that the majority (70%) of ChatGPT conversations are not work-related (based on OpenAI’s categorization), though both work and personal discussions are rising over time.

As per the report:

“The three most common Conversation Topics are Practical Guidance, Seeking Information, and Writing, collectively accounting for about 77% of all ChatGPT conversations. Practical Guidance has remained constant at roughly 29% of overall usage. Writing has declined from 36% of all usage in July 2024 to 24% a year later. Seeking Information has grown from 14% to 24% of all usage over the same period.”

For clarity, “Practical Guidance” in this context relates to how-to advice, tutoring or teaching, while “Seeking information” encompasses specific informational queries, product insights and recipes, among others.

It’s interesting to note the change in these trends over time, and how ChatGPT is rising as an alternative to Google for search and discovery.

The report also looks at the different purposes of ChatGPT usage, splitting the various queries into either:

• Asking – Seeking information to help make better decisions
• Doing – Getting ChatGPT to perform tasks for you (e.g. writing an email, writing code)
• Expressing – Uses that are neither asking nor doing, usually involving personal reflection

As you can see in this chart, people are looking to get ChatGPT to undertake tasks on their behalf less over time, with information seeking being the most common usage.

It’s interesting to consider how ChatGPT is assisting people with their discovery and decision-making processes, which is likely reflective of AI tools more broadly, and how people are looking to utilize AI companions in different applications.

Does this mean that AI tools are not as popular for, say, writing as many anticipated? And if more people are looking to ChatGPT to give them guidance on how they think, what does that mean for critical thought, and how such tools might shape opinions?

Some interesting considerations stemming from these latest usage stats.

You can download OpenAI’s “How People Are Using ChatGPT” report here.

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OpenAI has published a new overview of how people are using ChatGPT, and how usage of its conversational AI tool is evolving over time, which provides some interesting insight into what people are looking to use the tool for, and how that relates to broader trends.

The study is based on an analysis of 1.5 million conversations in the app over the last three years, providing a huge pool of usage data to determine key trends.

You can download the full report for yourself here, but in this post, we’ll take a look at some of the key notes.

First off, the report looks at the overall growth in usage of ChatGPT, which has risen from a million active users in late 2022, to 700 million weekly active users today.

That’s no surprise, with ChatGPT quickly becoming synonymous with AI usage in general, driving more and more interest in the tool.

The data also shows that the majority (70%) of ChatGPT conversations are not work-related (based on OpenAI’s categorization), though both work and personal discussions are rising over time.

As per the report:

“The three most common Conversation Topics are Practical Guidance, Seeking Information, and Writing, collectively accounting for about 77% of all ChatGPT conversations. Practical Guidance has remained constant at roughly 29% of overall usage. Writing has declined from 36% of all usage in July 2024 to 24% a year later. Seeking Information has grown from 14% to 24% of all usage over the same period.”

For clarity, “Practical Guidance” in this context relates to how-to advice, tutoring or teaching, while “Seeking information” encompasses specific informational queries, product insights and recipes, among others.

It’s interesting to note the change in these trends over time, and how ChatGPT is rising as an alternative to Google for search and discovery.

The report also looks at the different purposes of ChatGPT usage, splitting the various queries into either:

• Asking – Seeking information to help make better decisions
• Doing – Getting ChatGPT to perform tasks for you (e.g. writing an email, writing code)
• Expressing – Uses that are neither asking nor doing, usually involving personal reflection

As you can see in this chart, people are looking to get ChatGPT to undertake tasks on their behalf less over time, with information seeking being the most common usage.

It’s interesting to consider how ChatGPT is assisting people with their discovery and decision-making processes, which is likely reflective of AI tools more broadly, and how people are looking to utilize AI companions in different applications.

Does this mean that AI tools are not as popular for, say, writing as many anticipated? And if more people are looking to ChatGPT to give them guidance on how they think, what does that mean for critical thought, and how such tools might shape opinions?

Some interesting considerations stemming from these latest usage stats.

You can download OpenAI’s “How People Are Using ChatGPT” report here.

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A quick update for those using Meta’s Page Insights API, with Meta now set to merge more of its data into its “Views” metric.

In November last year, Meta announced that Facebook would be switching to “Views” as its primary metric, in alignment with shifting user behaviors and how they’re reflected in its engagement data.

That followed Instagram also moving to “Views” as its primary metric, with all of Meta’s data tools now providing enhanced view data as a cumulative engagement stat, while shifting away from others, including “plays,” “impressions” and “accounts reached.”

And now, Meta’s updating its Page Insights API to also reflect the same.

As per Meta:

“To continue to align the functionality of the Page Insights API with the Facebook app and Meta Business Suite, we’re deprecating the `impressions` metric. This metric will be replaced by the `views` metric on all API versions.”

In addition to this, Meta’s also getting rid of its “page fans” insights:

“With the migration of all Facebook Pages to the new Pages experience, the Page Insights tab for classic Pages has been fully deprecated as of November 1, 2023. As part of this deprecation, we are deprecating the `page fans` metrics.”

So two more metrics will soon be gone from your third-party analytics platforms, with “Views” taking over as the primary focus.

Meta says that the shift towards views aims to create a single distribution metric for all content types that’s calculated in the same way across Facebook and Instagram.

That, ideally, will facilitate a more streamlined, and understandable way to compare your content performance across both apps, with “Views” now measuring all types of consumption behavior.

Given that this has been in place within Meta’s own system for some time, the change here should be minor, but it’s another data update of note for your Facebook and IG planning.

Meta says that once the change is implemented, the API will return an invalid metric error when calling any of these metrics.

So again, your third party Facebook and Instagram tools will soon shift to views as the main focus, while losing access to these additional elements.

More information here.

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