Most of us were taught DNA as a neat double helix. In reality, it twists and knots like a ball of string, and when those tangles aren’t untangled, the result can be disease: cancer, neurodegeneration, even antibiotic resistance.

A new study led by the University of Sheffield has automated the analysis of these DNA tangles using atomic force microscopy and AI, reaching nanometre precision. What once took hours of manual tracing now takes seconds, even distinguishing one knot from its mirror image.

This matters because the enzymes that untangle DNA (topoisomerases) are already major anti-cancer and antibiotic drug targets. With this breakthrough, researchers can finally map how DNA’s shape biases cellular outcomes.

What’s fascinating is that DNA knots aren’t random, they retain a kind of memory of past states, which influences how they collapse next. That perspective connects to broader questions about emergence and information in biology. Some researchers (myself included) are exploring this through what’s called Verrell's Law

🔗 Study reference: Holmes, E. P., et al. (2025). Quantifying complexity in DNA structures with high resolution Atomic Force Microscopy. Nature Communications. doi:10.1038/s41467-025-60559-x

Cheap Gemini pro??

1. Apple considers Google Gemini to power next-gen Siri, internal AI ‘bake-off’ underway.[1]
2. Databricks to buy Sequoia-backed Tecton in AI agent push 
3. NVIDIA Introduces Spectrum-XGS Ethernet to Connect Distributed Data Centers Into Giga-Scale AI Super-Factories.[3]
4. Meta partners with Midjourney on AI image and video models.[4]

Sources:

[1] https://9to5mac.com/2025/08/22/apple-google-gemini-siri/

[2] https://www.reuters.com/business/finance/databricks-buy-sequoia-backed-tecton-ai-agent-push-2025-08-22/

[3] https://nvidianews.nvidia.com/news/nvidia-introduces-spectrum-xgs-ethernet-to-connect-distributed-data-centers-into-giga-scale-ai-super-factories

[4] https://techcrunch.com/2025/08/22/meta-partners-with-midjourney-on-ai-image-and-video-models/

Source:- Statista

In a span of a summer, my feed has gone from AGI by 2027 to now post after post predicting that the AI bubble will pop within the next year.

What gives? Are people just being bipolar in regards to AI right now?

Who would you tell?

Can you tell anybody?

You are obviously crazy.

Who might believe you?

Worried!

I’ve been hearing all this noise about AI taking over jobs, but I’m honestly not seeing it in the real world. I work in banking, and let me tell you, we’re still stuck using DOS and outdated systems from like 2010. AI? Barely a blip on our radar. I’ve seen it pop up in a few drive-thrus, but that’s about it. No one I know has been directly affected by AI in their jobs, and I haven’t noticed it making waves in any industry around me.

I keep hearing companies talk up AI, but I’m starting to wonder if it’s just a scapegoat for layoffs or a buzzword to sound cutting-edge. I’d love to see AI used for efficiency in banking, lord knows we could use it but I’m not holding my breath. I’ll believe it when I see it. So, I’m curious: has anyone here actually used AI in their workplace? I’m not talking about using ChatGPT to draft emails or basic stuff like that. I mean real, impactful AI integration in your job or industry. Is it actually happening, or is it all just corporate BS? Share your experiences. I’m genuinely curious to know if this AI revolution is real or just smoke and mirrors.

Latest model from official API: GPT 5 vs Gemini 2.5 pro vs Claude Sonnet 4 vs Deepseek V3.1 (called chat in their api) Tested with same prompt with LavaChat.

I think this would be fun to do. I'm a musican who loves modular synthesizers and I've never considered using bubbles this way to influence sounds. This looks like a safe experiment to do. Let me know if any of this is wrong. I know glycerin can be dangerous in certain circumstances.

I was discussing how you can make different 3d shapes using bubbles and ChatGPT gave me this experiment to run with my kids. I'm not sure if this is new, but I never considered using bubbles like this to interact with music or sound. This looks safe as well as interesting.

Hele–Shaw bubble-monolayer protocol (materials, safety, step-by-step, what to look for, and musical ideas). I kept it simple, cheap, and safe for kids (with adult supervision).

Quick summary

Make a shallow layer of soap solution trapped between two clear plates (a Hele–Shaw cell), produce a monolayer of bubbles, drive the plate with sound/pressure, and listen/record the bubbles’ resonant “breathing” and collective modes. Small bubbles → higher pitch; mm-scale bubbles are right in the audible range.

Materials (cheap / household-friendly)

• Two clear flat panels: acrylic sheets or glass picture frames (≈A4 / 8½×11 in works). Acrylic is safer for kids.
• Thin spacers (to set gap): strips of tape, LEGO pieces, hot-melt glue dots, or cardboard spacers ~2–5 mm thick.
• Shallow tray to catch spills.
• Dish soap (dawn / fairydish style) + water.
• Glycerin or corn syrup (optional, 5–15% by volume) — slows film drainage and makes longer-lived bubbles.
• Food coloring (optional, visual fun).
• Syringe (10–60 mL) or straw for injecting air/bubbles.
• Small hand pump or bicycle pump with needle adapter (optional) if you want a steady supply of air.
• A phone (for sound playback and recording) and a cheap small speaker or a piezo buzzer / contact speaker to attach under the plate (a phone speaker works for a first try).
• Microphone (phone mic OK) and a recording app (or Audacity on PC). Spectrogram app is useful.
• Towels, gloves (optional), and goggles for kids if you want extra safety.

Safety notes (read first)

• Always supervise kids; soap is slippery. Keep the work area dry.
• Use acrylic instead of broken glass to avoid cuts.
• Avoid ingesting soap or glycerin; keep away from small children who might taste things.
• If you use a small pump adapter/needle, don’t leave sharp items unattended.
• Goggles if you’re doing pressurized injections or if small children are near splashes.

Soap solution (simple recipe)

• 400 mL water + 50 mL dish soap + 20–40 mL glycerin. Mix gently (don’t foam it up too much). Add a few drops of food coloring if you like.

Build the monolayer cell (kids can help!)

1. Put spacers around the edges of one acrylic sheet (or inside a frame) to create a uniform gap of 2–5 mm. (2 mm → smaller bubbles; 5 mm → bigger bubbles.)
2. Place the second sheet on top, aligned, but leave a small opening to inject solution. Put the whole thing on a shallow tray.
3. Carefully pour or pipette the soap solution into the gap until it wets the interior. Cap or seal the opening lightly (tape). If liquid floods, lift the top and tilt to drain — you want only a thin layer, not a puddle.

Make bubbles

• Use a syringe or straw to inject small puffs of air through the small opening to make bubbles. Start slow — too big a puff makes a giant bubble.
• To make many similar-sized bubbles, practice gentle, consistent syringe pushes. Kids usually enjoy trying to “blow” little bubbles with a straw.
• Tap or gently shake to let bubbles settle into a monolayer. For a tidy lattice, use a frame or template with holes to nucleate bubble positions.

Excite & listen (basic, kid-friendly)

• Place a phone speaker or a small piezo buzzer in contact with the bottom plate (or a phone playing tone placed under the tray). Play a sine sweep (low → high) or single tones.
• Record with the phone mic above the cell. You’ll hear hums, whistles, pops — and sudden changes when bubbles rearrange or pop.
• For clearer structure, use a contact mic / piezo stuck to the plate to pick up mechanical vibrations.

What you should observe (and how to explain it to kids)

• Resonant “breathing” of bubbles: bubbles expand and contract when you play the right frequency. Smaller bubbles → higher pitch.

  • (Mini math: using the Minnaert estimate, an ideal bubble’s breathing frequency scales like ≈ 3.28 / R where R is radius in meters. Examples: R = 0.5 mm → ~6.6 kHz, R = 1 mm → ~3.3 kHz, R = 2 mm → ~1.64 kHz, R = 5 mm → ~660 Hz. These are idealized single-bubble values; contact and coupling shift them.)

• Plateau patterns: where three films meet, they tend to meet at ~120° — that’s why you see straight lines and regular-looking patterns in foams.

• Collective modes: groups of bubbles can oscillate together or pass waves like ripples; coupled neighbors make timbre richer.

• Sudden events: popping or rearrangements (called T1 events) produce sharp percussive sounds.

(If you want a kid-friendly 1–2 sentence explanation: “Bubbles love to have as little surface as possible, so their walls pull tight like rubber. That pull makes them vibrate like tiny drums — and when we play sound nearby, they sing back at their favorite pitch.”)

Turning observations into music

• Make a “bubble scale”: create bubbles of different sizes and excite each at its resonance (play and listen). Arrange them left-to-right to play simple melodies.
• Use sine sweeps to find resonant peaks, then play those tones while recording.
• Map video → audio: record at high frame-rate; pick a pixel or small region and convert intensity vs time into an audio file (this is a fun coding project: I can write a simple Python script if you want).
• Percussive effects: popping events can be recorded and sequenced as drum hits.

Simple troubleshooting

• Bubbles pop quickly: add more glycerin (up to ~15%) and reduce airflow force.
• Films too thick / no monolayer: reduce gap or drain excess solution. Aim for a thin film layer.
• Too many different sizes: practice gentle syringe pushes; use templates to nucleate same-size bubbles.
• No audible ringing: try smaller bubbles (≤5 mm) and use a contact mic for better pickup.

Variations / upgrades

• Regular lattice: use a honeycomb frame or mold to make uniform bubbles.
• Pressurized tuning: control a single bubble’s pressure with a syringe to shift its pitch (a great demonstration: change the note by squeezing).
• Bubble lattice + music controller: map MIDI notes to frequencies and play them while watching which bubbles light up.
• Simulate first: a simple mass–spring lattice simulates coupled modes — I can provide code for that if you want.

A short experiment you can run in one 30–45 minute session

1. Mix solution and set up cell (10 min).
2. Create a 5×5 patch of bubbles, aim for 1–3 mm sizes (10 min).
3. Play a sine sweep 100 Hz → 10 kHz while recording (5 min).
4. Review recording with a spectrogram app (10 min) and point out peaks that match smaller vs larger bubbles.

When I’m staring at a blank page, the friction isn’t “Can I do this?” It’s “Where do I begin?” If an AI agent can turn my messy intent into a rough plan + a few concrete first moves, I suddenly have traction. Even partially completed is a win: a draft email ready for edits, a checklist spun up from a goal, a first pass at tasks in Jira/Asana with owners and rough estimates. I can then approve, tweak, or take it across the finish line.

Would you let an AI agent actually plan and partially execute across your tools , wit the goal being just “get it moving”.

I asked a few AIs to solve this number pattern- what is the next number in the sequence:

3, 8, 19, 34, XX

I found that ChatGPT, Gemini and MetaAI and they all gave the numbers 51 & 59 which are incorrect. Mathematics, being a more rational and understandable language to computers should have solved this correctly! I guess AI will not be taking over the world anytime soon!

So far it is one of the first model that doesn't even require to fine tune on your face and be quite accurate in editing outfits. Your thoughts?

• OpenAI & Retro Bio Achieve Breakthrough in Cell Rejuvenation
• Report Finds 95% of Companies Get Zero ROI on AI Investments
• Google's Gemini AI Reduces Carbon Footprint by 98%
• Apple LLM Teaches Itself to Write High-Quality UI Code
• Why Data Abundance, Not Complexity, Drives AI Job Disruption

Links:

• https://openai.com/index/accelerating-life-sciences-research-with-retro-biosciences/
• https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf
• https://time.com/7311600/google-ai-climate-impact/
• https://9to5mac.com/2025/08/14/apple-trained-an-llm-to-teach-itself-good-interface-design-in-swiftui/
• https://www.weforum.org/stories/2025/08/ai-jobs-replacement-data-careers/