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Comparison · ai-assistants
Recall vs mlr3
A side-by-side editorial comparison of Recall and mlr3 — release velocity, themes, recent moves, and the top alternatives to consider.
Recall vs mlr3: at a glance
What is Recall?
Handwriting and screenshots become searchable cards, and the extension reaches Safari
Recall's August release is the broadest in months. OCR turns photos, screenshots and handwritten notes into real cards; the browser extension now runs on Safari and Edge alongside Chrome and Firefox, with connection editing inside the extension; chat proposes questions drawn from the saved library; and content can be added ten URLs at a time or by drag and drop. This follows a July that moved search into the full library page with text and AI modes searching reader content, notes and quizzes rather than titles.
What is mlr3?
mlr3 is hardening the seams where its abstractions meet real learners
Releases arrive every few weeks and read as a systematic audit of the Learner interface. Recent versions added a native_model binding and a predict_raw flag so users can reach the underlying package's model and raw prediction, gave encapsulated learners a wall-clock deadline alongside the existing timeout, and removed the deprecated Task$divide(). A run of fixes addresses correctness at the boundary - factor level ordering that inverted binary probabilities, fallback learners losing state, misaligned probability columns.
Recall vs mlr3: editorial side-by-side
Recall
6.3AI-ASSISTANTS
Handwriting and screenshots become searchable cards, and the extension reaches Safari
◆ Current state
Recall's August release is the broadest in months. OCR turns photos, screenshots and handwritten notes into real cards; the browser extension now runs on Safari and Edge alongside Chrome and Firefox, with connection editing inside the extension; chat proposes questions drawn from the saved library; and content can be added ten URLs at a time or by drag and drop. This follows a July that moved search into the full library page with text and AI modes searching reader content, notes and quizzes rather than titles.
◆ Where it's heading
Two threads have been converging all summer. One widens what can enter the library — social posts, Apple News, text and Markdown files, and now anything a camera can photograph. The other makes what is already inside retrievable: full-content search, personas, cross-card chat, and now suggested questions. OCR closes the last major gap on the input side, since paper was the one source that could not get in.
◆ Prediction
The mobile search overhaul is explicitly promised and is the most likely next release. Suggested questions plus full-content search point toward retrieval quality inside chat becoming the next area of investment.
mlr3
0.0AI-ASSISTANTS
mlr3 is hardening the seams where its abstractions meet real learners
◆ Current state
Releases arrive every few weeks and read as a systematic audit of the Learner interface. Recent versions added a native_model binding and a predict_raw flag so users can reach the underlying package's model and raw prediction, gave encapsulated learners a wall-clock deadline alongside the existing timeout, and removed the deprecated Task$divide(). A run of fixes addresses correctness at the boundary - factor level ordering that inverted binary probabilities, fallback learners losing state, misaligned probability columns.
◆ Where it's heading
The framework is maturing from wrapping models to being accountable for what happens when wrapping goes wrong. Structured Mlr3Error and Mlr3Warning classes, conditions stored on the learner log, and messages replaced by conditions all point at making failures programmatically inspectable rather than printed. In parallel, escape hatches to the upstream model are being formalised instead of left to users digging into internals.
◆ Prediction
Expect the remaining deprecated surface to follow Task$divide() out, and further work on encapsulation and fallback behaviour, which is where most recent fixes have clustered. The raw and native_model accessors suggest more of the upstream model will be surfaced deliberately.
Alternatives to Recall and mlr3
Other ai-assistants products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Recall or mlr3.
Ollama
A release train of small runtime wins between model drops
ClearML
ClearML is filling in the hyperdataset lifecycle while hardening the SDK against what it loads.
Baseten
Baseten is selling to the labs that build models, not just the developers who call them.
Gemini
Between a BTS tie-in and free student plans, Gemini quietly moves into a Waymo
Perplexity
Perplexity is selling access to other people's models, and now repricing them weekly.
Recent activity from Recall and mlr3
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 7h agoRecallOCR turns images into cards; extension reaches Safari and Edge ⚡
- 15d agoRecallSearch moves into the library and reads full content
- 27d agoRecallSocial saves rebuilt; table view and 62 AI languages
- 1mo agoRecallUse Case Hub launches as a guide library
- 1mo agoRecallInstagram and LinkedIn saving, plus text and Markdown upload
- 2mo agoRecallCustom Personas set standing instructions for chat
- 2mo agomlr3Fallback learner state and probability alignment fixes
- 2mo agomlr3Encapsulated learners gain a deadline; Task$divide() removed
- 4mo agomlr3Raw upstream predictions preserved; binary probability fix
- 5mo agomlr3Log messages replaced with conditions
- 6mo agomlr3native_model accessor and structured warning/error logs
- 8mo agomlr3Mlr3Error and Mlr3Warning classes introduced
Frequently asked questions
What is the difference between Recall and mlr3?
They serve adjacent needs but don't currently overlap on shipped themes. Recall is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Recall better than mlr3?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Recall is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other ai-assistants products to evaluate alongside.
What are the best alternatives to Recall?
Top Recall alternatives in ai-assistants are ranked by recent ship velocity. Browse the "Recall alternatives" section above for the current picks, or visit /alternatives/getrecall for the full list with editorial commentary on each.
What are the best alternatives to mlr3?
Top mlr3 alternatives in ai-assistants are ranked by recent ship velocity. Browse the "mlr3 alternatives" section above for the current picks, or visit /alternatives/mlr3 for the full list with editorial commentary on each.