The ABC in Australia feels so opinionated and tilted to the “left” side of politics whenever I’ve watched it on the TV. And it may just have been that news show or the specific host but it makes it not enjoyable to watch when it seems there’s always an “angle” and negative undertones and people constantly having an axe to grind. I’d personally like a bit more neutral news that also leans a little more on the positive and inspiring side.
>The ABC in Australia feels so opinionated and tilted to the “left” side of politics whenever I’ve watched it on the TV. And it may just have been that news show or the specific host but it makes it not enjoyable to watch when it seems there’s always an “angle” and negative undertones and people constantly having an axe to grind. I’d personally like a bit more neutral news that also leans a little more on the positive and inspiring side.
I dont see any bias in their journalism, but they have a tendency to just accept everything at face value. They will also shop around for experts that support their opinions. One person will write an article about housing referring to housing experts, and get one view, and then a few years later another will instead quote a public housing expert getting another view. Theres never any "Lets test the quality of each expert and try and figure out whats true"
4 corners and foreign correspondant however are still absolute top tier journalism. Its a shame they dont apply those standards everywhere.
A recent, prominent example is [1] where they edited footage to make it look like a soldier was shooting at an innocent civilian. They then appointed a 40 year abc/sbs veteran to investigate the incident who unsurprisingly found no wrong doing.
All of this on a topic that isn't even super political...
Granted they are still probably the best journalists in the country, but when you can't trust them to not alter primary evidence, or admit real fault when something has gone wrong, you cant really trust them for much.
For day to day stuff I still find them an ok source, it just needs to be taken with a very heavy dose of salt.
Their biggest fault was giving back the filing cabinet.
>where they edited footage to make it look like a soldier was shooting at an innocent civilian.
In your link the ABC is claiming the footage wasnt edited by them. I mean its still a bit of weak journalism to publish it. Did that ever get resolved either way?
> In your link the ABC is claiming the footage wasnt edited by them.
I'll admit I don't fully understand what they were claiming/how it changed over time but they later issued an apology for the incident [1].
From what I can work out the thrust of the abc claim is "don't blame our journalists, the editors on multiple occasions accidentally did this for no reason at all and we then failed to catch it".
Then midway through the apology they pivot to blaming twitter, or at least that is the flow of the guardian article.
I'm from Asana so I'm probably biased too :) and I agree single-player agents are easier, but multi-player agents that understand end to end workflows etc. are very powerful. That's what we've built and yes it took a lot of thought and time to built it in a way that it would be privacy conscious and not leak the wrong thing to the wrong people etc. I haven't player with Buzz yet but signed up and admire them for thinking differently and trying to build something interesting.
But isn't there the raw intelligence of a smart model and then the practical intelligence fuelled by how many parameters it has? You probably will barely be able to fit a 70 billion parameter model on a phone in 3-4 years let alone a 2+ trillion parameter model... so it depends on what you call intelligence
I'm not willing to believe in phone-based frontier models anytime soon. Though, Gemma 4 12B is a beast that runs comfortably on the current top of the line phones (or would run fine if allowed to run, I think there's some kind of 6GB limit on iOS, and 12B is ~7GB). I'll believe in three years we'll be able to run ~30B models on the best phones. That's 16GB in a 4-bit quantization, and I believe ~30B models will be competitive with 120B models of today, based on the curve we've been on. Qwen 27B and Gemma 4 31B are competitive with much larger models of a couple years ago.
How would it compare to Wispr Flow? I recently started using it and it feels so much more robust than anything out there (and in fact the one in iOS and MacOS 26 seemed pretty poor in comparison)... and do we know if Wispr Flow uses the Whisper tech behind the scenes or if they have their own model etc?
Surely it’ll be an issue some day for other space activities with all the SpaceX kit up there? I know space is very large :) but surely it’d be hard to scan, calculate and control trajectories of millions of orbiting tiny things when you’re launching rockets and things? A spacex satellite almost crashed into the Chinese space station some years ago and the Chinese had to perform an evasive manoeuvre I believe
With modern automation and AI, tracking and adjusting paths is better every year. Also, anything with malfunctioning movement will quickly descend and burn up in the atmosphere at that very low orbit.
Satellites flying at 360km (the target altitude for starlink V3) deorbit very quickly without regular burns. Dead starlink satellites are guaranteed to come down within 5 years.
Yes and I'll become another space industry. Cleanup. Sort of like how (coal/ocean/etc) pollution is both a problem and multi billion dollar a year industry.
A cool detail in the article that you can look up in the news is the French government investing €650m in AI, including technology (not just implementation, training and licensing it seems). Hope some of it is for further funding and equity in Mistral, and that other European countries follow suit. Even better if there was a great non-profit or B-Corp European alternative to the US and Chinese frontier/SOTA labs.
Is this Apple encouraging developers to go through their api abstraction layer to use LLMs so that when they launch their own (which I think we’ve heard they’ve been spending lots of money on training and might be somehow involved with Siri or current Apple AI?) that they can easily help devs make a seamless transition? Or is it just a developer nicety or something else?
Apple has some clever mechanics to protect user data. I had to work with App tracking stuff lately and their approach to keeping user details private with anonymized cohorts (SKAN, Differential Privacy) before reporting tracking events to third party platforms was surprisingly well thought out. There is value in having them in your loop if you care about privacy.
My read of the ATT stuff is basically that it forced all the apps to use meta ad tracking because they’re the only ones who figured out how to serve relevant ads despite it.
Right, the lesson here is that if you make rules with exploitable loopholes youre probably only going to end up strengthening malicious actors who are willing to exploit loopholes.
This is support for a new framework that ships with reality/mac/iPad/watch/tv/iOS 27 (and that they've promised to open-source later in the year, so presumably you'll also be able to lean on this if you ship Swift on your backend).
The framework's whole deal is that it lets you use the same API to target either the device built-in models, the Apple-hosted online models (Private Cloud Computer), or write your own shims to call out to arbitrarily hosted online models.
You can then dynamically route your calls to a different kind of model/provider, using system APIs, without having to write your own abstraction layer over "I want to use local model for this, but I want to use Claude for that", or having to integrate your own API integration with Anthropic/OpenAI APIs.
It abstracts things like tool calling in one place; and has a bunch of other niceties/oddities (it keeps the same "transcript" going, even if you dynamically switch providers/models during a session) and some other things.
The cynic (or realist?) in my thinks this abstraction layer is Apple's way of making sure that users give their own Apple Intelligence credit for the underlying LLM functionality, even if another company is actually providing the LLM.
Yeah, Apple just designs and writes the SoC, CPU, graphics unit, neural unit, compiler (Swift), OS, graphics layer, 3D API, core libs from graphics to persistence, filesystem, broadband chip, and a few more things besides...
AI models in the end are just commodities the computer using public is not going to pay for them directly, in short, they’re not gonna bail out OpenAI, Meta, Google, Microsoft, Anthropic.
A dark, but not totally unfair take: It makes it easier for Apple to take payment for the models others provide, and even allows Apple, if they want to, to use the data to build a dataset for training their own models based on how users use third party models. It's only on Apple devices this API is used, so they split up the market by not letting developers use the same system if they want things to work on iOS, locking users even more in.
> Requests go directly from your app to the Claude API; Apple is not in the request path and does not see prompts or responses. Usage is billed to your Anthropic account at standard API pricing. Your app decides when to use Claude and when to use Apple's on-device model: pass whichever model you want to each session.
Maybe they plan to have the providers pay for being the default model? So basically, what Google is doing right now for search engines. The difference however is that Google is making money with additional search requests while AIs are (as of now) losing money with additional requests. I don't see the business case for them yet though.
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