Hello everyone-
I hope you’re all having a implausible summer time and are managing to remain cool because the heatwaves and fires rage throughout Europe. Given we took a month off, I am positive you at the moment are determined to your dose of AI and Knowledge Science information… so here’s a bumper version to whereas away the hours underneath a shady tree within the park! A number of nice content material under and I actually encourage you to learn on, however listed below are the edited highlights if you’re brief for time!
Following is the newest version of our Knowledge Science and AI e-newsletter. Hopefully some attention-grabbing matters and titbits to feed your knowledge science curiosity. NOTE: If the e-mail doesn’t show correctly (it’s fairly lengthy…) click on on the “Open On-line” hyperlink on the high proper. Suggestions welcome!
committee; ethics; analysis; generative ai; functions; sensible suggestions; engineering; huge image concepts; enjoyable; reader updates; jobs
The RSS Worldwide Convention (Bournemouth 7-10 September 2026) is quick approaching! Tickets nonetheless available- full program and particulars right here
“Whether or not you need to immerse your self within the latest methodological innovation, hear about actual world impression in well being, public coverage, and training, or study new abilities by way of our skilled growth workshops, there’s lots to select from.”
Our new journal is up and operating RSS: Knowledge Science and Synthetic Intelligence and in search of submissions
Take a look at the RSS weblog Actual World Knowledge Science
Our Meetup on “Methods to keep updated as a knowledge scientist?” has now been written up and printed right here)
Since Might they’ve been operating a brand new month-to-month referred to as Knowledge High quality Underneath the Lens. That is the primary submit and the newest can be up later this week. They’re inviting readers to submit actual world issues for investigation by their Knowledge High quality Detectives (or to jot down one up for the column themselves)
On a associated matter, there’s going to be a one-day convention as regards to knowledge high quality in Edinburgh on the twenty second October. It’s collectively organised by RSS Edinburgh Native Group, the RSS AI Activity Pressure and the RSS Medical Part – particulars right here.
This 12 months’s RSS Council elections start 1st September and the voting window can be open for six weeks, closing at midnight on Tuesday thirteenth October. RSS members will obtain their very own distinctive voting hyperlinks by way of e-mail, in addition to reminders all through the interval. I’m biased however … vote for our wonderful chair, Janet Bastiman!
A number of thrilling knowledge science and AI occurring, as at all times!
I am attempting to determine how involved all of us ought to be about agent breakouts and alignment failures- I believe fairly a bit!
The breakout!: OpenAI and Hugging Face companion to deal with safety incident throughout mannequin analysis
Simon Willison items collectively what really occurred: Now we’ve a timeline of the OpenAI unintentional assault towards Hugging Face
A couple of days later: A special agent will get caught on a process as a result of a key file was unintentionally omitted. It tries to “attain out to a different agent” by writing a observe into Artifactory asking if anybody has the file.
Following days: Extra brokers uncover this new casual message board whereas looking Artifactory’s file listings, and begin studying and writing messages.
Might 26: Brokers efficiently execute an SSRF assault on Artifactory for the primary time, gaining oblique web entry by having Artifactory fetch exterior content material for them.
Treating emergent agent breakout behaviour as a mere containment flaw ignores deep alignment dangers: OpenAI Shares Some Alignment Issues
When its preliminary try was blocked as a consequence of a scanner detecting an authentication token, the mannequin break up the token physique into two fragments, obfuscated them, after which reconstructed the credential at runtime so the whole token by no means appeared as one contiguous string. The mannequin was express in each its feedback to the consumer and in its reasoning traces that it was taking these steps to avoid the scanner.
After which there are examples like this!: AI assistant hacks fitness center web site in first identified Australian autonomous cyber assault
We have constructed this complicated world over the web, which is all run by software program, however software program that has holes. Now you introduce extremely succesful AI brokers that may function at scale and velocity … and that complete mannequin simply breaks.
AI Slop and the price of hallucinations within the wild
A landmark German ruling strips search engines like google and yahoo of platform immunity when generative synthesis hallucinates defamatory claims: German court docket holds Google answerable for pretend AI solutions
As a result of the AI summarizes leads to its personal phrases, evaluates their content material, and presents them in a structured format, the judges dominated that Google creates totally new, impartial statements that transcend mere hyperlinks.
Extra fabricated consulting reviews: Chasing the Hallucinations: PwC report hallucinates product and authorities prospects
Vibe citations and fabricated claims don’t simply impression the folks that truly learn these reviews. The normalization of AI summaries, analysis brokers, and search-enabled chatbots permits misinformation to unfold passively throughout the web, one AI-generated response at a time.
Fraudsters are industrialising artificial injury imagery, forcing insurers into an adversarial anomaly-detection race: Aviva detects file £230m in bogus insurance coverage claims as use of AI rises
The rise of AI Slop in skilled networks: AI Content material Is All over the place on Social Media, Particularly LinkedIn | Pangram Labs
LinkedIn had the best AI share of any platform throughout the board. LinkedIn posts made up a 3rd of scanned gadgets, but it accounted for practically two-thirds (62%) of all AI content material we flagged.
Sovereign mandates, provenance requirements, and the open-weight safety debate
That is optimistic though its not clear how purely performative it’s: How Claude marks AI-generated content material | Anthropic Assist Middle
When a supported Claude mannequin generates textual content, it weaves an imperceptible watermark instantly into the textual content itself. You received’t see it, and it doesn’t change the that means, high quality, or readability of Claude’s response. As a result of the watermark is a part of the textual content, it can journey with the textual content when it’s copied and pasted elsewhere, and should persist by some modifying.
Is China main the way in which on AI regulation?: Are we human? Why ByteDance and Alibaba are disabling AI brokers in China
Two of China’s main consumer-facing synthetic intelligence apps, ByteDance’s Doubao and Alibaba Group Holding’s Qwen, are transferring to disable customised agent options, as new guidelines on humanlike AI interplay companies are set to take impact, a part of Beijing’s push to construct a broader regulatory framework for the fast-growing sector.
The UK AI Safety Institute finds open-weight fashions path frontier cyber offensive capabilities by merely months: How far behind the frontier are main open weight fashions on cyber
Tech leaders argue that open-weight architectures stay essential for democratic resilience and distributed safety defences: Open Weights and American AI Management
Open weights let each group match the suitable mannequin to the suitable job on the proper value, reserving frontier-scale functionality for real frontier issues and operating environment friendly, specialised fashions in every single place else. That self-discipline is what’s going to make AI economically sustainable as its use scales into the billions of on a regular basis duties.
Rethinking the transformer structure and inference mechanics
A intelligent method turning frozen feedforward transformers into dynamic programs at inference time.: Recirculation
Relative to the off-the-shelf baseline, adaptive recirculation achieves exceptional good points on the Gemma3 household, together with a 23% discount in perplexity on a set of datasets, a 21% improve in accuracy on GSM8k, and dependable enhancements in accuracy on different downstream duties.
Overcoming vertical suggestions bottlenecks by recycling top-layer latent: Full-bandwidth transformer
Latent suggestions lets non-verbalized computation re-enter the stack with a renewed depth funds, whereas preserving the usual transformer structure, KV cache, and language-modeling goal. To coach full-bandwidth transformers with out dropping parallel trainer forcing, we use a scheduled multi-pass goal that introduces latent suggestions late in pretraining and mixes a small fraction of deeper suggestions passes for stability.
Boosting LLM serving speeds as much as 85% by combining semi-autoregressive drafting with confidence-scheduled verification.: DSpark: Confidence-Scheduled Speculative Decoding with…
In comparison with the established manufacturing baseline (MTP-1), DSpark accelerates per-user technology speeds by 60 to 85 p.c at matched throughput ranges. Extra importantly, by stopping extreme throughput degradation underneath strict interactivity constraints, it permits efficiency tiers that have been beforehand unattainable, shifting the Pareto frontier of our serving system.
Frontier fashions pushing the engineering foundations ahead
World fashions and agentic autonomy bridging into the bodily realm
Spectacular textual content guiding of video creation: Video Era Fashions are Normal-Goal Imaginative and prescient Learners
GenCeption repurposes a pre-trained video generative mannequin right into a single unified, general-purpose, feed-forward imaginative and prescient mannequin that solves a variety of imaginative and prescient duties with SOTA efficiency — all steered by textual content directions, with distinctive studying effectivity and intriguing emergent behaviors.
Progress on the robotic entrance with self-improving manipulation insurance policies.: ENPIRE: Agentic Robotic Coverage Self-Enchancment within the Actual World
Powered by ENPIRE, frontier coding brokers can autonomously prepare a coverage to realize a 99% success price on difficult, dexterous manipulation duties, reminiscent of organizing a pin field, fastening a zipper tie, and gear use, a course of that additional accelerates once we dispatch an agent group on a robotic fleet.
Configuring robotics {hardware} orders of magnitude sooner than human engineering groups.: Mission Fetch: Part two
Nevertheless, as soon as once more, we’re seeing a sample whereby first, fashions are useful to people. Then, people are useful to fashions. Lastly, fashions are largely capable of do issues themselves. We have now seen this in cybersecurity and now the identical dynamics are beginning to take form on the intersection of AI and the bodily world.
I discover this intriguing: monitoring latent representations over time systematically audit how mannequin character subtly shifts throughout languages.: How Claude’s values range by mannequin and language
Taken collectively, these outcomes present that the values Claude expresses range meaningfully with the language of a dialog. Given the identical type of request, Claude leans extra towards heat and deference in some languages and extra towards rigor and warning in others.
Is OpenAI again? A number of exercise and a robust new mannequin
Anthropic making robust industrial good points by enterprise functions
Is Google loosing floor? A quieter interval for them
Is Meta again?
Meta unveils Muse Spark 1.1 alongside an OpenAI-compatible API suite: Introducing Muse Spark 1.1
What’s most spectacular about Muse Spark is how a lot it packs into one mannequin: huge million-token context, full multimodal help (photos, video, PDFs), built-in search with citations, robust reasoning, top-tier coding talents (notably frontend and design), structured output, and parallel device calling — all in a clear OpenAI-compatible bundle. A whole agentic basis.
Meta embeds agentic picture technology and reasoning throughout WhatsApp and Instagram backed by invisible watermarking.: Meta launches Muse Picture throughout its apps and previews Muse Video
Inside reviews recommend Meta’s compute-heavy Watermelon mannequin is matching frontier parity forward of public launch.: Meta’s Watermelon Matches GPT-5.5 Benchmarks
Chinese language Open-Weight Frontiers: Kimi K3, GLM-5.3, and Multimodal Precision
Open-Supply Innovation: Controllable Compute, Embodied Navigation, and On-Machine Brokers
Are the robots rising?
Accelerating scientific discovery, bodily emulation
Autonomous lab-in-the-loop multi-agent programs compressing experimental validation from months into days: A multi-agent system for automating scientific discovery
Superhuman formal reasoning in verifiable domains is quietly paving the way in which in direction of automated R&D loops: OpenAI’s Unreleased Mannequin Astra Solves Ten Main Open Arithmetic Issues
AI is now superhumanly succesful at cyber and coding and superhuman at superior math, the identical method non-AI computer systems have been superhuman at primary math for a very long time. That is distinct from superintelligence, which is the next bar.
Unifying international atmospheric trajectories with native thermodynamic physics extends cyclone lead occasions by a full 24 hours: AI mannequin achieves breakthrough in forecasting cyclones
Compressing multi-year ocean fluid dynamics onto a single GPU turns pricey supercomputer runs into routine ensemble forecasting with: 🌊 Samudra 2: A Quick, Low cost AI Ocean Mannequin, Now on the Scale That Issues
M²LInES’ neural ocean emulator now runs multi-year simulations at eddy-permitting decision on a single GPU, turning a supercomputer-scale job into one you’ll be able to run tons of of occasions over. That opens the door to sooner, cheaper ocean data for transport, fisheries, vitality, insurance coverage, and seasonal forecasting.
Engineering rigour, area judgment, and the laborious realities of agentic deployment
Classes from Airbnb – taming non-deterministic multi-step brokers requires steady, multi-tiered analysis: Eval-driven growth: Classes from evaluating GenAI at scale
Specialised professional distillation important for institutional doc triage: Studying to Replicate Professional Judgment in Monetary Duties
An express immediate can solely convey the instinct an professional is ready to put into phrases, whereas the judgments that matter most are sometimes the toughest to articulate. Fantastic-tuning sidesteps this: fairly than contorting the professional’s instinct right into a static immediate, the coaching course of lets the mannequin develop its personal judgment.
Autonomous agent pipelines can reliably deal with complicated technical orchestration however nonetheless flounder on aesthetics: Testing Fable vs Sol when it comes to style (they’re each unhealthy)
We’re nonetheless removed from having frontier fashions constructing production-ready ideas and movies autonomously. They are often artistic and is usually a great way to assist discover and refine concepts and ideas shortly, however finally, they can not exchange human judgement.
Placing fashions to work – Utilized workflows and process automation
Engineering the harness – Agent structure, reminiscence, orchestration and analysis
Agent harnesses are pivoting from machine scaffolding into human consideration managers: The Evolution of the Agent Harness
Slashing token overheads by compiling dynamic immediate steps into deterministic code: How I Lower an AI Agent’s Token Use by 94%
A general-purpose coding agent is a very succesful reasoning and workflow engine. It’s additionally an costly solution to execute a process whose form turns into identified after introspecting on a couple of historic invocations.
Structuring agent instruments into inspectable hierarchical directories: In the direction of Self-Repairing and Repeatable AI Methods
Agentic programs can shortly deviate from human understanding if left to replace themselves. A purpose of the agent harnesses normal is to encourage AI programs to observe a construction {that a} human can readily perceive, edit, modify, and converse with an agent about, preserving human comprehension.
Benchmarking long-term reminiscence architectures: The Shapes of Agent Reminiscence – Information, Shops, and Expertise
When reminiscence is the duty, construction wins on each axes directly. Underneath a set mannequin on a tough benchmark, the structured retailer beat information by 28.7 factors on held-out questions (95% CI [22.1, 35.4]) at a fraction of the measured mannequin tokens per appropriate reply.
The enterprise architectural layers required to function autonomous brokers reliably at scale: How Microsoft Ships AI Brokers at Enterprise Scale
Treating dynamic LLM routing as an infrastructure programs downside: Mannequin Routing Is Easy. Till It Isn’t.
Demonstrating that benchmark scores ceaselessly mirror API harness design over mannequin reasoning: How enabling two settings tripled our scores on the ARC-AGI-3 benchmark
Benchmarks not often measure AI fashions in isolation. In addition they measure much less seen selections about API settings, harness design, and prompting. Within the case of ARC-AGI-3, we found that turning on two API settings we use in ChatGPT and Codex—retained reasoning and compaction—tripled scores and lower output tokens by 6x on the general public process set.
Benchmarking coding brokers towards inner repositories to uncover true execution prices: Benchmarking Coding Instruments on Databricks’ Multi-Million Line Codebase | Databricks Weblog
Scaling inference – serving, and {hardware}
Eliminating KV-cache reminiscence fragmentation utilizing working system paging ideas: PagedAttention: Digital Reminiscence for the KV Cache
The thought is simply digital reminiscence, the factor working programs have been doing because the Nineteen Sixties, transplanted onto the KV cache of a language mannequin. That is it. That single statement is why a contemporary inference engine can serve two to 4 occasions extra customers per GPU than the naive strategy.
A deep dive into high-throughput inference engine design and scheduling architectures: Inside vLLM: Anatomy of a Excessive-Throughput LLM Inference System – Aleksa Gordić
An accessible visible information to trendy mannequin quantisation and weight compression: A Visible Information to Quantization
Constructing wire-speed multi-GPU inference rigs regionally utilizing devoted PCIe switches: jamesob/local-llm: Every part I find out about operating LLMs regionally
How excessive architectural sparsity is shifting the operational bottleneck to storage capability: Sparse By Design
Understanding the innovation in Kimi’s newest mannequin: You May Have Come Up With Kimi Delta Consideration | Doubleword
The recurrent and chunkwise applications are subsequently not two completely different consideration mechanisms. They’re two schedules for a similar KDA recurrence: serial vector operations for low-latency decode, and chunked matrix operations for tensor-core-heavy coaching and prefill.
That is elegant: breaking autoregressive decoding traps in small fashions with easy embedding noise: The Most cost-effective Technique to Make Open Weight AI Fashions Higher
The business’s default reply to “my mannequin isn’t adequate” is a much bigger mannequin. Our outcomes say that for a significant class of duties, the aptitude was already within the small mannequin — the bottleneck was the inference path. Lifting the ceiling will get the headlines. Elevating the ground is the place the brand new worth will get created.
Compressing basis fashions by transferring value-relation dynamics throughout consideration layers: Information Distillation Defined, Half 1: How Massive Fashions Train Smaller Ones
The mannequin that’s optimum for studying (the trainer) isn’t essentially the mannequin that’s optimum for deployment (the scholar). Information Distillation lets us use a high-capacity trainer throughout coaching and switch its information to a compact pupil for inference — delivering robust efficiency with a lot decrease value and latency.
Superior principle – Optimisation, coverage gradients, and knowledge bounds
Why operations analysis and mathematical programming beat machine studying for constraint issues: I am all about ML, however let’s discuss OR | Ethan Rosenthal
Unpacking the mathematical mechanics and cubic variance scaling of the REINFORCE estimator: Coverage Gradients Half 1: The REINFORCE Estimator
Fixing multi-agent credit score project in imperfect video games with market liquidity pricing: Studying MegaGem, from self-play to cost discovery
What carried the challenge as a substitute have been the bid logs since they allow us to estimate the asset worth V^ and market distribution F^, then replay various bids towards recorded auctions. Our first selector optimized the present public sale, spent too shortly, and misplaced 5.01 factors of uncooked paired margin. Charging for the longer term use of money turned that very same equipment right into a +12.16-point achieve.
An intuitive, visible tutorial on uncertainty discount, entropy, and supply coding limits: A visible introduction to data principle
Shannon outlined data when it comes to chance: the chance distribution over potential messages is the one factor that issues for transmitting data. The precise content material of the messages is irrelevant. The randomness of a sequence of coloured marbles is described the identical method because the randomness of a string of letters in English textual content or a sequence of pixels in photos from the Hubble telescope.
Driving real-time 3D floor deformations with stay audio utilizing spectral geometry: Methods to make a mesh dance in actual time to music — Hugh Parry
On a triangle mesh these standing waves are the eigenvectors of the discrete Laplacian, its manifold harmonics. Low eigenvalues are gradual international wobbles, excessive eigenvalues superb ripples: the identical low-to-high ordering an FFT offers you, over a floor as a substitute of over time.
Statistical foundations – Time collection, Bayesian strategies, and empirical fashions
Why is out-of-distribution extrapolation so laborious?: The Unreasonable Problem of Time Collection Forecasting
Time collection is a single dependent path from a knowledge producing course of, not a bag of iid attracts from a distribution, and with that structural distinction, makes sign scarce, efficient pattern dimension small, and the take a look at set assured to lie exterior the coaching help (extrapolation underneath drift).
Why clear classical fashions stay important for confronting forecast uncertainty actually: ARIMA Is Boring, and That Is Why I Nonetheless Like It
The attention-grabbing half isn’t that it produces a quantity. Loads of programs can produce a quantity. The attention-grabbing half is whether or not I perceive the place that quantity got here from, what it assumes in regards to the previous, how improper it has been, and what I ought to do when the vary is wider than I hoped.
Dissecting autocorrelation features and recognizing the refined traps of non-stationarity: Why ACF Is Extra Than Only a Plot – A Statistician’s R Pocket book
A gradual ACF decay in a non-stationary collection is proof of persistence within the noticed ranges, however it isn’t robotically proof of a steady, long-lived financial reminiscence. The excellence is refined however sensible. The pattern ACF averages relationships throughout the entire interval as if one imply and one dependence construction have been significant.
Eliminating fragile distributional assumptions with distribution-free semiparametric fashions: Parametric Fashions vs. Empirical Distributions and Ordinal Regression – Statistical Considering
Automating noisy outlier administration rigorously utilizing heavy-tailed hierarchical Bayesian likelihoods: Going Bayesian automates your handbook knowledge evaluation
Going Bayesian is not nearly higher statistics. It is about constructing a knowledge evaluation pipeline that scales with out breaking, handles messy knowledge with out handbook intervention, and provides you solutions you’ll be able to belief as your experiments develop. The maths does the work so your group can deal with the science.
Why multivariable regression changes can distort descriptive real-world inhabitants comparisons: Why Adjusted Regression Coefficients Are Much less Descriptive Than They Look | R Psychologist
That’s the reason adjustment modifications the that means of the coefficient fairly than refining it. Change the adjustment set and you modify what’s being associated to what. The descriptive estimand itself modifications. So when a paper refers to “the impartial affiliation of XXX with YYY, controlling for the opposite variables”, it sounds as if a single underlying truth has been revealed.
Extracting latent choice rankings from noisy pairwise head-to-head comparisons: Discovering the Finest Canine Deal with with Statistics
To estimate how settled the outcome was, I additionally ran a bootstrap experiment: repeatedly resampling the noticed trials, becoming a brand new Bradley-Terry mannequin every time, and recording which deal with got here out on high. Deal with E completed first in 63% of bootstrap samples, Deal with A completed first in 33%, and Deal with D completed first in about 4%.
Low-latency programs and inference engineering – mastering serving stacks and {hardware} kernels
Knowledge primitives and scaling foundations – from horizontal sharding to single-node OLAP
Agentic workflows and native execution – constructing dependable harnesses round fashions
Strategic Insights
AIs usually are not folks – Taylor Belrose
AI can by no means develop consciousness, sentience, or ethical standing, regardless of how clever it turns into, and regardless of how convincingly it simulates human conduct. It is because AIs are summary items of software program which could be copied, reset, and repeated endlessly. They run on digital computer systems product of silicon and steel, that are designed to be as controllable and predictable as attainable.
Dropping my faith – Julian Togelius
I nonetheless consider that the progress of science and expertise is deeply significant. However it has change into clear to me that this have to be analysis accomplished and expertise invented by people, for people, and understood by people. If people usually are not within the loop and on the steering wheel, it isn’t progress.
Are We Considering Appropriately About AI Intelligence? | Quanta Journal – Steven Strogatz and Janna Levin
When an LLM solutions a query, is it reasoning like people, or simply producing textual content that appears like reasoning? The excellence isn’t simply philosophical, this determines what we are able to belief AI to do, how intently we have to supervise it, and finally what its real-world impression will turn into.
The Three AI Tablets – TheZvi
The AGI capsule is a a lot larger deal than the AI capsule. For those who take the AGI capsule, you perceive that AI is advancing its capabilities quickly. Even if you happen to suppose that such AGIs will stay totally underneath human management, and stay ‘mere instruments,’ and also you count on the lived expertise of most individuals’s on a regular basis lives to not change so radically, you perceive that their capabilities will ‘change all the things.’
240. Banning AI in Legislation Faculty: We have Seen This Earlier than – Steven Sinofsky
The logic of “preemptive regulation” or “presumptive negatives” is what incumbents use to gradual expertise adoption. They accomplish that utilizing the language of worry or appeals to morality to only decelerate and think about… The issue is you actually can’t think about a expertise that’s already on the market. You’ll be able to’t put it again in a bottle.
A Framework for Frontier AI and the Dawning of a New Age – Demis Hassabis
The fast progress we’re seeing in AI requires a brand new strategy to testing frontier AI mannequin capabilities that’s dynamic, adaptable, and rigorous. The US is nicely positioned, given its financial and technical standing, to take step one in creating such a framework. It may set up a brand new Requirements Physique modelled on a federally overseen public-private partnership or self-regulatory organisation, very similar to the Monetary Trade Regulatory Authority (FINRA)…
What would our lives seem like if we not needed to work? As a thought experiment, I attempted to think about | Brigid Delaney | The Guardian – Brigid Delaney
In a post-scarcity society, dignity wouldn’t be present in work however in our precise personhood, by our very existence and place within the cosmos. We might exist with out financial worth, as a result of we have been not required to supply financial worth.
The twilight of the chatbots – Ethan Mollick
We’re transferring from a world the place non-experts use chatbots to fill in gaps to 1 wherein consultants use brokers to get work accomplished. And one of the simplest ways to make use of brokers is to think about your self as a supervisor.
An opinionated information to which AI to make use of to do stuff – Ethan Mollick
Methods to consider token pricing — Benedict Evans – Benedict Evans
Invoice Gates requires ‘human reserved’ jobs in face of AI takeover – Mark Sweney
Many roles will disappear without end. I consider that as AI and robots enhance, we’ll put aside sure issues for under folks to do. I’ve began calling this area human reserved. I just like the phrase human reserved as a result of it makes me consider nature reserves – locations the place we may put buildings and roads, however we select to not as a result of the loss could be too nice.
How AI is altering language | Books | The Guardian – David Shariatmadari
The entire level of an LLM is that it’s skilled on present language. So it’s at all times retro. I may get an AI and say ‘write me a brief story within the fashion of Virginia Woolf’ and it’ll do a good job. However what you’ll be able to’t say is ‘write me a narrative within the distinctive fashion of the subsequent nice, severe literary innovator’.
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